{"id":2163,"date":"2026-09-08T15:45:35","date_gmt":"2026-09-08T15:45:35","guid":{"rendered":"https:\/\/lean-app.com\/?p=2163"},"modified":"2026-09-08T17:55:59","modified_gmt":"2026-09-08T17:55:59","slug":"perdre-du-poids-avec-chatgpt","status":"publish","type":"post","link":"https:\/\/lean-app.com\/da\/perdre-du-poids-avec-chatgpt\/","title":{"rendered":"Perdre du poids avec ChatGPT, \u00e7a marche ? \u00c9tude : 291 r\u00e9ponses, jusqu&rsquo;\u00e0 1 260 kcal d&rsquo;\u00e9cart"},"content":{"rendered":"<div id=\"lvm-shell\"><style>#lvm-shell{display:contents;--rule:#e6e2dc;--ink:#111;--muted:#6b6b6b;--font-display:-apple-system,\"SF Pro Display\",\"Segoe UI\",Roboto,Arial,sans-serif;font-family:var(--font-display)}#lvm-shell .nav{position:sticky;top:0;z-index:50;background:rgba(255,255,255,.86);backdrop-filter:saturate(180%) blur(14px);-webkit-backdrop-filter:saturate(180%) blur(14px);border-bottom:1px solid var(--rule)}#lvm-shell .nav-row{max-width:1160px;margin:0 auto;display:flex;align-items:center;gap:14px;padding:10px 22px;box-sizing:border-box}#lvm-shell .nav-brand{display:flex;align-items:center;gap:9px;text-decoration:none;color:var(--ink)}#lvm-shell .nav-brand img{width:28px;height:28px;border-radius:7px;object-fit:cover}#lvm-shell .nav-brand span{font-weight:600;font-size:18px;letter-spacing:-.01em}#lvm-shell .nav-spacer{flex:1}#lvm-shell .nav-link{color:var(--muted);text-decoration:none;font-size:14px}#lvm-shell .nav-link:hover{color:var(--ink)}#lvm-shell .nav-stores{display:flex;gap:6px;align-items:center}#lvm-shell .nav-stores a{display:block;line-height:0}#lvm-shell .nav-stores img{height:28px;width:auto;border-radius:5px;transition:transform .15s}#lvm-shell .nav-stores a:hover img{transform:translateY(-1px)}@media (max-width:768px){#lvm-shell .nav-row{padding:8px 18px;gap:8px}#lvm-shell .nav-link{display:none}#lvm-shell .nav-stores img{height:24px}#lvm-shell .nav-stores{gap:4px}}@media (max-width:380px){#lvm-shell .nav-stores img{height:22px}}<\/style><header class=\"nav\"><div class=\"nav-row\"><a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/da\/\" aria-label=\"Lean forside\"><img loading=\"lazy\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" decoding=\"async\"><span>Lean<\/span><\/a><span class=\"nav-spacer\"><\/span><a class=\"nav-link\" href=\"https:\/\/lean-app.com\/da\/tdee-calculator\/\">TDEE-beregner<\/a><div class=\"nav-stores\"><a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&amp;utm_medium=blog&amp;utm_campaign=etude-chatgpt\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download i App Store\"><img loading=\"lazy\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\"><\/a><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&amp;utm_source=seo&amp;utm_medium=blog&amp;utm_campaign=etude-chatgpt\" target=\"_blank\" rel=\"noopener\" aria-label=\"Tilg\u00e6ngelig p\u00e5 Google Play\"><img loading=\"lazy\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\"><\/a><\/div><\/div><\/header><\/div>\n<style>#lean-etude{--lean-sticky-top:52px}<\/style><style>\n#lean-etude {\n  --bg: #F3F0EB;\n  --white: #fff;\n  --ink: #222326;\n  --muted: #66635F;\n  --pink: #FF456C;\n  --hot: #FF2D6E;\n  --violet: #DCD0F4;\n  --night: #191A1D;\n  --line: rgb(34 35 38 \/ 15%);\n  --ease: cubic-bezier(.22,1,.36,1);\n  --pointer-x: 0;\n  --pointer-y: 0;\n  --scene-scroll: 0;\n  position: relative;\n  isolation: isolate;\n  container-type: inline-size; 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width: 80px; height: 80px; grid-row: 1; grid-column: 1; font-size: 25px; font-weight: 500; letter-spacing: -.02em; font-variant-numeric: tabular-nums; }\n#lean-etude .le-behavior-list li > span:not(.le-behavior-meter) { grid-row: 2; font-size: 12px; line-height: 1.6; }\n#lean-etude .le-behavior-meter { grid-row: 1; grid-column: 1; width: 80px; height: 80px; border-radius: 50%; background: conic-gradient(var(--pink) var(--percent),rgb(128 128 128 \/ 18%) 0); mask: radial-gradient(farthest-side,transparent calc(100% - 3px),#000 calc(100% - 2.5px)); transform: rotate(-90deg); }\n#lean-etude .le-behavior-meter i { display: none; }\n#lean-etude .le-insight { max-width: 68ch; margin: 45px 0 0 auto; padding-top: 30px; border-top: 1px solid var(--line); font-size: 17px; line-height: 1.7; }\n#lean-etude .le-simple .le-insight { color: #D2CFCA; }\n#lean-etude .le-simple .le-insight strong { color: var(--white); }\n#lean-etude .le-complet { padding-top: 100px; }\n#lean-etude .le-complet .le-chart { background: var(--white); }\n#lean-etude .le-comparison { margin-top: 75px; }\n#lean-etude .le-comparison-title { margin-bottom: 32px; font-size: 30px; }\n#lean-etude .le-comparison-stats { display: grid; grid-template-columns: repeat(3,minmax(0,1fr)); gap: 0; border-top: 1px solid var(--line); border-bottom: 1px solid var(--line); }\n#lean-etude .le-comparison-stats li { padding: 35px 35px 35px 0; }\n#lean-etude .le-comparison-stats li + li { padding-left: 35px; border-left: 1px solid var(--line); }\n#lean-etude .le-comparison-stats strong { display: block; margin-bottom: 22px; font-size: clamp(44px,5.5cqi,74px); font-weight: 500; line-height: .95; letter-spacing: -.035em; white-space: nowrap; }\n#lean-etude .le-comparison-stats small { font-size: 18px; font-weight: 500; letter-spacing: -.01em; }\n#lean-etude .le-comparison-stats span { display: block; max-width: 27ch; font-size: 13px; line-height: 1.6; }\n#lean-etude .le-comparison-stats li:last-child strong { color: var(--hot); }\n#lean-etude .le-suivi { --line: rgb(255 255 255 \/ 17%); color: #F6F3EF; background: var(--night); padding-bottom: 0; }\n#lean-etude .le-suivi h2 { max-width: 27ch; font-size: clamp(35px,5cqi,65px); }\n#lean-etude .le-time-headline { display: block; margin-top: 14px; color: #FF7795; }\n#lean-etude .le-time-intro { max-width: 51ch; margin: 0 0 60px auto; font-size: 17px; line-height: 1.7; color: #D5D1CB; }\n#lean-etude .le-time-stage { --time-progress: 0; display: grid; grid-template-columns: 1fr 1fr; column-gap: 100px; align-items: start; margin-bottom: 75px; }\n#lean-etude .le-time-dial { position: sticky; top: calc(var(--lean-sticky-top,0px) + 110px); padding-bottom: 40px; text-align: center; }\n#lean-etude .le-dial-face { position: relative; display: flex; flex-direction: column; align-items: center; justify-content: center; width: 100%; max-width: 390px; aspect-ratio: 1; margin: 0 auto; border-radius: 50%; background: radial-gradient(circle at 40% 40%,#353035 0%,#222124 55%,#191A1D 72%); }\n#lean-etude .le-dial-face::before { content: \"\"; position: absolute; inset: 0; border-radius: 50%; background: conic-gradient(from -90deg,#FF7795 calc(var(--time-progress)*100%),rgb(255 255 255 \/ 14%) 0); mask: radial-gradient(farthest-side,transparent calc(100% - 2px),#000 calc(100% - 1.5px)); }\n#lean-etude .le-dial-face::after { content: \"\"; position: absolute; inset: 15px; border: 1px solid rgb(255 255 255 \/ 7%); border-radius: 50%; }\n#lean-etude .le-dial-unit { font-size: 13px; }\n#lean-etude .le-dial-day { margin-top: 0; color: #FF7795; font-size: clamp(80px,12cqi,170px); font-weight: 400; line-height: 1.05; letter-spacing: -.04em; font-variant-numeric: tabular-nums; }\n#lean-etude .le-dial-caption { display: block; margin-top: 28px; font-size: 12px; color: #BEBAB4; }\n#lean-etude .le-timeline { padding-top: 0; }\n#lean-etude .le-timeline li { position: relative; min-height: 215px; padding: 25px 0 45px 33px; border-top: 1px solid var(--line); }\n#lean-etude .le-timeline li::before { content: \"\"; position: absolute; top: 30px; left: 0; width: 7px; height: 7px; border-radius: 50%; background: #777477; transition: background-color .3s; }\n#lean-etude .le-timeline li.is-current::before { background: #FF7795; box-shadow: 0 0 16px rgb(255 69 108 \/ 35%); }\n#lean-etude .le-timeline strong { display: block; margin-bottom: 20px; font-size: 17px; font-weight: 500; line-height: 1.3; }\n#lean-etude .le-timeline strong b { font-size: inherit; font-weight: inherit; }\n#lean-etude .le-timeline li > span { display: block; max-width: 34ch; font-size: 21px; line-height: 1.5; letter-spacing: -.02em; }\n#lean-etude .le-timeline li.is-current > span { color: #FFB0C2; }\n#lean-etude .le-checklists { display: grid; grid-template-columns: 1fr 1fr; gap: 85px; padding: 55px 0 80px; border-top: 1px solid var(--line); }\n#lean-etude .le-checklist h3 { max-width: 20ch; margin-bottom: 32px; font-size: 30px; font-weight: 500; }\n#lean-etude .le-checklist ul { display: grid; gap: 19px; }\n#lean-etude .le-checklist li { display: flex; gap: 14px; align-items: baseline; font-size: 14px; line-height: 1.7; color: #D2CFC9; }\n#lean-etude .le-checklist li > span:first-child { flex: 0 0 18px; color: #FF7795; font-size: 14px; }\n#lean-etude .le-checklist-yes li > span:first-child { color: #A9D7C5; }\n#lean-etude .le-verdict { margin: 0; padding: 75px max(40px,calc((100% - 1280px)\/2)); background: #DCD0F4; color: var(--ink); font-size: clamp(26px,3.5cqi,45px); font-weight: 400; letter-spacing: -.03em; line-height: 1.35; text-wrap: pretty; }\n#lean-etude .le-verdict > strong { display: block; max-width: none; margin-bottom: 34px; font-size: 13px; font-weight: 550; line-height: 1.6; letter-spacing: 0; }\n#lean-etude .le-app { display: grid; grid-template-columns: 1fr 1fr; gap: 30px 80px; background: var(--white); }\n#lean-etude .le-app .le-section-heading { margin: 0; }\n#lean-etude .le-app h2 { max-width: 15ch; font-size: 46px; }\n#lean-etude .le-app-intro { grid-column: 1; font-size: 16px; }\n#lean-etude .le-app-panel { grid-column: 2; grid-row: 1\/3; align-self: center; padding: 0 0 0 45px; border-left: 1px solid var(--line); }\n#lean-etude .le-feature-list { display: flex; flex-wrap: wrap; gap: 12px 20px; padding-bottom: 28px; margin-bottom: 30px; border-bottom: 1px solid var(--line); }\n#lean-etude .le-feature { display: inline-flex; align-items: baseline; gap: 8px; font-size: 11px; }\n#lean-etude .le-feature::before { content: \"\"; flex: 0 0 6px; width: 6px; height: 6px; background: #FA256C; border-radius: 50%; }\n#lean-etude .le-feature-1::before { background: #FF8C00; }\n#lean-etude .le-feature-2::before { background: #E84D44; }\n#lean-etude .le-feature-3::before, #lean-etude .le-feature-4::before { background: #4CAF50; }\n#lean-etude .le-feature-4 { flex-basis: 100%; }\n#lean-etude .le-app-panel > strong { display: block; max-width: 22ch; margin-bottom: 18px; font-size: 25px; font-weight: 500; letter-spacing: -.025em; line-height: 1.25; }\n#lean-etude .le-app-panel > span { display: block; font-size: 13px; line-height: 1.75; color: var(--muted); }\n#lean-etude .le-store-links { display: flex; flex-wrap: wrap; gap: 18px; margin-top: 20px; }\n#lean-etude .le-store-links a { display: flex; align-items: center; min-height: 44px; font-size: 12px; font-weight: 600; line-height: 1.4; }\n#lean-etude .le-donnees h2 { max-width: 19ch; }\n#lean-etude .le-data-list { display: grid; grid-template-columns: repeat(2,minmax(0,1fr)); column-gap: 50px; row-gap: 0; margin-bottom: 35px; }\n#lean-etude .le-data-record { padding: 28px 0; border-top: 1px solid var(--line); }\n#lean-etude .le-data-heading { margin-bottom: 17px; font-size: 16px; font-weight: 500; line-height: 1.5; text-wrap: pretty; }\n#lean-etude .le-data-heading strong { font-weight: 700; }\n#lean-etude .le-data-values { font-size: 13px; line-height: 1.9; color: var(--muted); }\n#lean-etude .le-data-values strong { color: var(--ink); font-weight: 600; font-variant-numeric: tabular-nums; }\n#lean-etude .le-data-note { max-width: 85ch; margin: 18px 0; font-size: 13px; line-height: 1.8; color: var(--muted); }\n#lean-etude .le-data-note:last-child { margin-top: 25px; font-size: 11px; }\n#lean-etude .le-disclosure { border-bottom: 1px solid var(--line); }\n#lean-etude .le-disclosure summary { position: relative; display: block; list-style: none; min-height: 68px; padding: 24px 40px 24px 0; font-size: 17px; font-weight: 500; line-height: 1.4; letter-spacing: -.02em; cursor: pointer; }\n#lean-etude .le-disclosure summary::-webkit-details-marker { display: none; }\n#lean-etude .le-disclosure summary::before, #lean-etude .le-disclosure summary::after { content: \"\"; position: absolute; right: 4px; top: 33px; width: 14px; height: 1px; background: currentColor; transition: transform .25s var(--ease); }\n#lean-etude .le-disclosure summary::after { transform: rotate(90deg); }\n#lean-etude .le-disclosure[open] summary::after { transform: rotate(0); }\n#lean-etude .le-disclosure p { max-width: 75ch; margin: 0 0 22px; font-size: 14px; line-height: 1.8; color: var(--muted); }\n#lean-etude .le-disclosure ul { max-width: 80ch; margin: 0 0 24px; padding-left: 18px; list-style: disc; font-size: 13px; line-height: 1.8; }\n#lean-etude .le-disclosure li + li { margin-top: 13px; }\n#lean-etude .le-faq { display: grid; grid-template-columns: .65fr 1.4fr; gap: 0 70px; background: var(--white); }\n#lean-etude .le-faq .le-section-heading { grid-column: 1; grid-row: 1\/8; }\n#lean-etude .le-faq h2 { font-size: 43px; }\n#lean-etude .le-faq .le-disclosure { grid-column: 2; }\n#lean-etude .le-faq .le-disclosure:first-of-type summary { padding-top: 4px; }\n#lean-etude .le-faq .le-disclosure:first-of-type summary::before, #lean-etude .le-faq .le-disclosure:first-of-type summary::after { top: 13px; }\n#lean-etude .le-suite { color: #F6F4F1; background: var(--night); }\n#lean-etude .le-suite h2 { font-size: 35px; }\n#lean-etude .le-related { display: grid; grid-template-columns: repeat(2,minmax(0,1fr)); column-gap: 65px; row-gap: 0; }\n#lean-etude .le-related li { border-top: 1px solid rgb(255 255 255 \/ 18%); }\n#lean-etude .le-related a { position: relative; display: block; height: 100%; padding: 27px 45px 27px 0; font-size: 18px; font-weight: 500; line-height: 1.4; text-decoration: none; }\n#lean-etude .le-related a::after { content: \"\u2197\"; position: absolute; right: 0; top: 26px; font-size: 23px; transition: transform .25s var(--ease); }\n#lean-etude .le-related a span { display: block; margin-top: 14px; font-size: 12px; font-weight: 400; line-height: 1.7; color: #BFBAB5; }\n#lean-etude .le-suivi { padding: 0; }\n#lean-etude .le-suivi-inner { padding: 100px max(40px,calc((100% - 1280px)\/2)) 0; }\n@media (hover:hover) {\n  #lean-etude .le-profile-button:hover:not([aria-pressed=\"true\"]) { background: rgb(128 128 128 \/ 15%); }\n  #lean-etude .le-nav a:hover:not([aria-current]) { background: #E6E0D9; }\n  #lean-etude .le-explore:hover { transform: translateY(-2px); background: #3C3C3F; }\n  #lean-etude .le-related a:hover::after { transform: translate(3px,-3px); }\n}\n#lean-etude button:active, #lean-etude .le-explore:active { transform: scale(.96); }\n@container lean-study (max-width:1100px) {\n  #lean-etude .le-suivi-inner { padding-inline: 32px; }\n  #lean-etude .le-section { padding-inline: 32px; }\n  #lean-etude .le-ouverture { grid-template-columns: 1.05fr 1fr; }\n  #lean-etude h1 { font-size: 65px; }\n  #lean-etude .le-title-follow { font-size: 23px; }\n  #lean-etude .le-hero-scene { height: 585px; }\n  #lean-etude .le-sculpture { inset: 0 -25px auto; width: calc(100% + 50px); height: 570px; }\n  #lean-etude .le-answer { width: 150px; padding: 12px; }\n  #lean-etude .le-answer strong { font-size: 13px; }\n  #lean-etude .le-answer-0 { left: -5%; }\n  #lean-etude .le-answer-2 { right: 0; }\n  #lean-etude .le-answer-3 { left: -2%; }\n  #lean-etude .le-resume, #lean-etude .le-methode, #lean-etude .le-faq { column-gap: 40px; }\n  #lean-etude .le-method-stats { gap: 22px; }\n  #lean-etude .le-chart { gap: 0 30px; padding: 32px; grid-template-columns: minmax(165px,.7fr) minmax(0,1.8fr); }\n  #lean-etude .le-profile-title { font-size: 17px; }\n  #lean-etude .le-caption-gap { font-size: 26px; }\n  #lean-etude .le-behavior-list { gap: 25px; }\n  #lean-etude .le-comparison-stats strong { font-size: 56px; }\n  #lean-etude .le-time-stage { column-gap: 65px; }\n  #lean-etude .le-checklists { gap: 50px; }\n  #lean-etude .le-app { column-gap: 40px; }\n  #lean-etude .le-app-panel { padding-left: 30px; }\n  #lean-etude .le-verdict { padding-inline: 32px; }\n}\n@container lean-study (max-width:800px) {\n  #lean-etude .le-suivi-inner { padding: 74px 28px 0; }\n  #lean-etude .le-masthead { height: 82px; padding-inline: 28px; }\n  #lean-etude .le-section { padding: 74px 28px; }\n  #lean-etude .le-ouverture { padding-top: 28px; padding-bottom: 34px; gap: 0 12px; }\n  #lean-etude h1 { font-size: 51px; }\n  #lean-etude .le-eyebrow { font-size: 10px; margin-bottom: 22px; }\n  #lean-etude .le-title-follow { margin-top: 20px; font-size: 21px; }\n  #lean-etude .le-deck { font-size: 14px; }\n  #lean-etude .le-hero-scene { height: 530px; }\n  #lean-etude .le-sculpture { inset: 0 -20px auto; width: calc(100% + 40px); height: 520px; }\n  #lean-etude .le-answer { width: 133px; padding: 10px; }\n  #lean-etude .le-answer-name { font-size: 8px; }\n  #lean-etude .le-answer strong { font-size: 12px; }\n  #lean-etude .le-answer-0 { left: -4%; top: 19%; }\n  #lean-etude .le-answer-1 { right: 0; top: 6%; }\n  #lean-etude .le-answer-3 { bottom: 25%; left: -3%; }\n  #lean-etude .le-answer-4 { bottom: 12%; }\n  #lean-etude .le-hero-stats { gap: 24px; grid-template-columns: 1.2fr repeat(3,1fr); margin-top: 20px; }\n  #lean-etude .le-hero-stat > strong { font-size: 38px; }\n  #lean-etude .le-main-stat > strong { font-size: 49px; }\n  #lean-etude .le-main-stat > strong span { font-size: 15px; }\n  #lean-etude .le-hero-stat > span { font-size: 11px; }\n  #lean-etude h2 { font-size: 43px; }\n  #lean-etude .le-resume, #lean-etude .le-methode { grid-template-columns: .6fr 1fr; gap: 25px 40px; }\n  #lean-etude .le-summary-text { font-size: 15px; }\n  #lean-etude .le-summary-list li:first-child strong { font-size: 35px; }\n  #lean-etude .le-summary-list li { gap: 14px; grid-template-columns: 20px 1fr; }\n  #lean-etude .le-summary-verdict { padding-left: 34px; font-size: 14px; }\n  #lean-etude .le-method-stats { grid-template-columns: repeat(2,minmax(0,1fr)); gap: 28px; }\n  #lean-etude .le-method-note { font-size: 12px; }\n  #lean-etude .le-chart { gap: 0 24px; padding: 28px; }\n  #lean-etude .le-chart-caption { font-size: 10px; }\n  #lean-etude .le-caption-gap { font-size: 24px; }\n  #lean-etude .le-model, #lean-etude .le-range-value { font-size: 12px; }\n  #lean-etude .le-comparison-stats strong { font-size: 45px; }\n  #lean-etude .le-comparison-stats li { padding-right: 24px; }\n  #lean-etude .le-comparison-stats li + li { padding-left: 24px; }\n  #lean-etude .le-comparison-stats small { font-size: 14px; }\n  #lean-etude .le-time-stage { column-gap: 38px; grid-template-columns: .8fr 1fr; }\n  #lean-etude .le-timeline li > span { font-size: 18px; }\n  #lean-etude .le-app h2 { font-size: 38px; }\n  #lean-etude .le-verdict { padding: 60px 28px; }\n}\n@container lean-study (max-width:640px) {\n  #lean-etude .le-suivi-inner { padding: 60px 22px 0; }\n  #lean-etude .le-masthead { height: 76px; padding-inline: 22px; gap: 18px; }\n  #lean-etude .le-brand { font-size: 33px; }\n  #lean-etude .le-mast-caption { display: none; }\n  #lean-etude .le-mast-link { font-size: 10px; }\n  #lean-etude .le-section { padding: 60px 22px; }\n  #lean-etude .le-ouverture { display: grid; grid-template-columns: minmax(0,1fr); padding-top: 22px; padding-bottom: 30px; }\n  #lean-etude .le-hero-copy { display: contents; }\n  #lean-etude .le-ouverture .le-eyebrow { grid-row: 1; }\n  #lean-etude .le-ouverture h1 { grid-row: 2; }\n  #lean-etude .le-ouverture .le-hero-scene { grid-row: 3; }\n  #lean-etude .le-ouverture .le-deck { grid-row: 4; }\n  #lean-etude .le-ouverture .le-hero-actions { grid-row: 5; }\n  #lean-etude .le-ouverture .le-byline { grid-row: 6; }\n  #lean-etude .le-ouverture .le-hero-stats { grid-row: 7; }\n  #lean-etude h1 { font-size: clamp(40px,10.4cqi,62px); line-height: 1.04; font-weight: 650; }\n  #lean-etude .le-eyebrow { margin-bottom: 22px; font-size: 11px; }\n  #lean-etude .le-title-follow { max-width: 26ch; margin-top: 22px; font-size: 22px; }\n  #lean-etude .le-deck { margin-top: 21px; font-size: 14px; }\n  #lean-etude .le-hero-actions { margin-top: 22px; }\n  #lean-etude .le-explore { min-height: 44px; padding: 11px 21px; font-size: 12px; }\n  #lean-etude .le-byline { max-width: 57ch; margin-top: 20px; font-size: 9px; }\n  #lean-etude .le-hero-scene { height: 465px; margin-top: 17px; }\n  #lean-etude .le-sculpture { inset: -5px 0 auto; width: 100%; height: 470px; }\n  #lean-etude .le-answer { width: 138px; padding: 10px 12px; }\n  #lean-etude .le-answer-name { font-size: 8px; }\n  #lean-etude .le-answer strong { font-size: 12px; }\n  #lean-etude .le-answer-line { margin-top: 9px; }\n  #lean-etude .le-answer-0 { top: 36%; left: 0; }\n  #lean-etude .le-answer-1 { top: 5%; right: 0; }\n  #lean-etude .le-answer-2 { top: 41%; right: 0; }\n  #lean-etude .le-answer-3 { bottom: 19%; left: 0; }\n  #lean-etude .le-answer-4 { bottom: 9%; right: 0; }\n  #lean-etude .le-scene-label { bottom: 0; right: 0; font-size: 9px; }\n  #lean-etude .le-hero-stats { grid-template-columns: repeat(3,minmax(0,1fr)); gap: 30px 24px; margin-top: 35px; padding-top: 25px; }\n  #lean-etude .le-main-stat { grid-column: 1\/-1; display: flex; align-items: center; justify-content: space-between; gap: 20px; padding-bottom: 25px; border-bottom: 1px solid var(--line); }\n  #lean-etude .le-main-stat > strong { flex: 0 0 auto; margin: 0; font-size: 65px; }\n  #lean-etude .le-main-stat > strong span { display: block; margin-top: 8px; font-size: 16px; }\n  #lean-etude .le-main-stat > span { max-width: 19ch; font-size: 13px; }\n  #lean-etude .le-mini-stat > strong { font-size: 35px; }\n  #lean-etude .le-mini-stat > span { font-size: 10px; }\n  #lean-etude .le-nav { justify-content: space-between; gap: 0; padding: 7px 12px; }\n  #lean-etude .le-nav a { min-height: 44px; padding: 0 9px; font-size: 10px; }\n  #lean-etude h2 { font-size: clamp(35px,8.5cqi,48px); }\n  #lean-etude .le-section-label { font-size: 11px; margin-bottom: 18px; }\n  #lean-etude .le-section-heading { margin-bottom: 30px; }\n  #lean-etude .le-resume, #lean-etude .le-methode, #lean-etude .le-faq, #lean-etude .le-app { display: block; }\n  #lean-etude .le-resume h2 { max-width: 16ch; }\n  #lean-etude .le-summary-list li:first-child strong { font-size: 44px; }\n  #lean-etude .le-summary-list li { grid-template-columns: 18px 1fr; gap: 18px; padding-block: 22px; }\n  #lean-etude .le-summary-text { font-size: 16px; }\n  #lean-etude .le-summary-num { font-size: 13px; }\n  #lean-etude .le-summary-verdict { padding-left: 36px; margin-top: 10px; font-size: 14px; }\n  #lean-etude .le-methode h2 { max-width: 15ch; font-size: 36px; }\n  #lean-etude .le-method-stats { margin: 36px 0; grid-template-columns: repeat(4,minmax(0,1fr)); gap: 15px; }\n  #lean-etude .le-method-stats strong { margin-bottom: 12px; 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}\n  #lean-etude .le-comparison-stats strong { font-size: 40px; }\n  #lean-etude .le-verdict { padding-inline: 18px; font-size: 26px; }\n}\n#lean-etude .le-suivi { padding: 0; }\n@media (prefers-reduced-motion:reduce) {\n  #lean-etude *, #lean-etude *::before, #lean-etude *::after { animation: none !important; transition: none !important; scroll-behavior: auto !important; }\n  #lean-etude .le-sculpture { transform: none; }\n}\n@media print {\n  #lean-etude { background: #fff; color: #222326; font-size: 11pt; }\n  #lean-etude .le-masthead, #lean-etude .le-hero-scene, #lean-etude .le-nav, #lean-etude .le-progress, #lean-etude .le-chart-controls, #lean-etude .le-time-dial, #lean-etude .le-hero-actions { display: none !important; }\n  #lean-etude .le-section { width: 100%; padding: 24px 0; background: #fff; color: #222326; }\n  #lean-etude .le-chart[hidden] { display: grid !important; }\n  #lean-etude .le-chart { break-inside: avoid; border: 1px solid #ccc; }\n  #lean-etude .le-ouverture, #lean-etude .le-resume, #lean-etude .le-methode, #lean-etude .le-faq, #lean-etude .le-app, #lean-etude .le-time-stage { display: block; }\n  #lean-etude .le-timeline li { min-height: 0; padding: 16px 0; }\n  #lean-etude .le-verdict { margin: 0; padding: 24px; }\n  #lean-etude .le-disclosure::details-content { content-visibility: visible; }\n}\n\n<\/style>\n<article aria-labelledby=\"le-title\" id=\"lean-etude\" lang=\"fr\"><div aria-hidden=\"true\" class=\"le-progress\"><i><\/i><\/div><section class=\"le-section le-ouverture\" id=\"le-ouverture\"><div class=\"le-hero-copy\"><p class=\"le-eyebrow\">Unders\u00f8gelse \u00b7 Tabe sig med l&rsquo;IA<\/p>\n<h1 id=\"le-title\"><span class=\"le-title-line\">Tabe sig<\/span> <span class=\"le-title-line\">med ChatGPT,<\/span> <span class=\"le-title-accent\">virker det?<\/span> <span class=\"le-title-follow\">Vi stillede sp\u00f8rgsm\u00e5let 291 gange til 5 IA<\/span><\/h1><p class=\"le-deck\">Samme person, samme sp\u00f8rgsm\u00e5l, op til 1.260 kcal forskel. Her er, hvad AI&rsquo;erne svarer, og hvad de ikke kan g\u00f8re.<\/p>\n<div class=\"le-hero-actions\" data-visual-copy=\"\"><a class=\"le-explore\" href=\"#le-resume\">Udforsk unders\u00f8gelsen<\/a><span class=\"le-scroll-cue\">\u2193<\/span><\/div><p class=\"le-byline\">Uafh\u00e6ngigt studie af Lean-teamet, appen der genberegner dit forbrug hver dag ud fra dine m\u00e5linger \u00b7 9. september 2026 \u00b7 \u00c5bne data<\/p>\n<\/div><div aria-hidden=\"true\" class=\"le-hero-scene\" data-visual-copy=\"\"><img alt=\"Buste anatomique translucide, illustration de la d\u00e9pense \u00e9nerg\u00e9tique du corps\" class=\"le-sculpture\" loading=\"eager\" decoding=\"sync\" fetchpriority=\"high\" height=\"1400\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/09\/etude-chatgpt-hero-metabolism.webp\" width=\"1120\"\/><div class=\"le-scene-orbit\"><\/div><span class=\"le-scene-label\">P2 \u00b7 Simpel prompt<\/span><div class=\"le-answer le-answer-0\" style=\"--order:0\"><span class=\"le-answer-name\">ChatGPT (GPT-5.5)<\/span><strong>1.600 til 2.700 kcal<\/strong><i class=\"le-answer-line\"><\/i><\/div><div class=\"le-answer le-answer-1\" style=\"--order:1\"><span class=\"le-answer-name\">ChatGPT (GPT-5.4 mini)<\/span><strong>1.600 til 2.760 kcal<\/strong><i class=\"le-answer-line\"><\/i><\/div><div class=\"le-answer le-answer-2\" style=\"--order:2\"><span class=\"le-answer-name\">Gemini 3.7 Flash<\/span><strong>1.600 til 2.600 kcal<\/strong><i class=\"le-answer-line\"><\/i><\/div><div class=\"le-answer le-answer-3\" style=\"--order:3\"><span class=\"le-answer-name\">Gemini 3.1 Pro<\/span><strong>1.600 til 2.700 kcal<\/strong><i class=\"le-answer-line\"><\/i><\/div><div class=\"le-answer le-answer-4\" style=\"--order:4\"><span class=\"le-answer-name\">Claude Opus<\/span><strong>1.500 til 2.500 kcal<\/strong><i class=\"le-answer-line\"><\/i><\/div><\/div><ul class=\"le-hero-stats\"><li class=\"le-hero-stat le-main-stat\"><strong>1 260 <span>kcal<\/span><\/strong><span>forskel for samme profil, simpel prompt<\/span><\/li>\n<li class=\"le-hero-stat le-mini-stat\"><strong>0 %<\/strong><span>sp\u00f8rger om kropsfedt<\/span><\/li>\n<li class=\"le-hero-stat le-mini-stat\"><strong>97 %<\/strong><span>svarer med et &ldquo;stillesiddende \/ aktivt&rdquo; skema<\/span><\/li>\n<li class=\"le-hero-stat le-mini-stat\"><strong>14 %<\/strong><span>n\u00e6vner metabolisk tilpasning<\/span><\/li>\n<\/ul>\n<\/section>\n<nav aria-label=\"I denne unders\u00f8gelse\" class=\"le-nav\"><a href=\"#le-resume\">Resum\u00e9<\/a><a href=\"#le-simple\">Resultater<\/a><a href=\"#le-suivi\">Det egentlige sp\u00f8rgsm\u00e5l<\/a><a href=\"#le-donnees\">Data<\/a><a href=\"#le-faq\">FAQ<\/a><\/nav>\n<section aria-labelledby=\"le-resume-title\" class=\"le-section le-resume\" id=\"le-resume\"><header class=\"le-section-heading\"><span class=\"le-section-label\">Resum\u00e9<\/span><h2 id=\"le-resume-title\">Studiet p\u00e5 30 sekunder<\/h2><\/header>\n<ul class=\"le-summary-list\"><li><span class=\"le-summary-num\">1<\/span><span class=\"le-summary-text\"><strong>291 svar<\/strong> fra ChatGPT, Gemini og Claude p\u00e5 sp\u00f8rgsm\u00e5let &ldquo;hvor mange kalorier for at tabe sig?&rdquo;, for 6 identiske profiler.<\/span><\/li>\n<li><span class=\"le-summary-num\">2<\/span><span class=\"le-summary-text\">Simpel prompt (alder, v\u00e6gt, h\u00f8jde): den samme person f\u00e5r <strong>fra 1.500 til 2.700 kcal<\/strong> afh\u00e6ngigt af AI&rsquo;en og tidspunktet.<\/span><\/li>\n<li><span class=\"le-summary-num\">3<\/span><span class=\"le-summary-text\"><strong>0 %<\/strong> af svarene sp\u00f8rger om kropsfedt. <strong>97 %<\/strong> returnerer et \u201cstillesiddende \/ moderat \/ aktivt\u201d-gitter, formlen fra 1990.<\/span><\/li>\n<li><span class=\"le-summary-num\">4<\/span><span class=\"le-summary-text\">Fuld prompt (kropsfedt, skridt, sessioner): stadig <strong>650 kcal<\/strong> af forskel, og kropsfedt bruges kun i <strong>40 %<\/strong> beregningerne.<\/span><\/li>\n<li><span class=\"le-summary-num\">5<\/span><span class=\"le-summary-text\">Ingen AI f\u00f8lger op dagen efter: dagens skridt, m\u00e5ltider, termisk effekt, metabolisk tilpasning (<strong>14 %<\/strong> de n\u00e6vner det). Tallet er fastl\u00e5st p\u00e5 dag 1.<\/span><\/li>\n<\/ul>\n<div class=\"le-summary-verdict\"><strong>Dom.<\/strong> Det kan virke af held, ikke af metode: uden m\u00e5ling eller daglige opdateringer er svaret et populationsgennemsnit fastl\u00e5st den f\u00f8rste dag.<\/div><\/section>\n<section aria-labelledby=\"le-methode-title\" class=\"le-section le-methode\" id=\"le-methode\"><header class=\"le-section-heading\"><span class=\"le-section-label\">01 \u00b7 Metode<\/span><h2 id=\"le-methode-title\">Det, vi gjorde<\/h2><\/header>\n<ul class=\"le-method-stats\"><li><strong>6<\/strong><span>identiske profiler, fra den atletiske kvinde til den stillesiddende mand<\/span><\/li>\n<li><strong>2<\/strong><span>promptniveauer: simpel, derefter fuld<\/span><\/li>\n<li><strong>5<\/strong><span>forbruger-AI'er, frisk samtale hver gang<\/span><\/li>\n<li><strong>291<\/strong><span>tidsstemplede svar, offentliggjort som \u00e5bne data<\/span><\/li>\n<\/ul>\n<p class=\"le-method-note\">ChatGPT (GPT-5.5 og GPT-5.4 mini), Gemini (3.7 Flash og 3.1 Pro), Claude Opus. Fransk og engelsk, 2 til 3 gentagelser, uden nogen instruktion. Den sorte linje p\u00e5 graferne: m\u00e5let beregnet komponent for komponent ud fra de m\u00e5lte data (BMR p\u00e5 fedtfri masse, skridt, sessioner, TEF, underskud p\u00e5 500 kcal).<\/p>\n<\/section>\n<section aria-labelledby=\"le-simple-title\" class=\"le-section le-simple\" id=\"le-simple\"><header class=\"le-section-heading\"><span class=\"le-section-label\">02 \u00b7 Resultat 1<\/span><h2 id=\"le-simple-title\">Simpel prompt: fra 1.500 til 2.700 kcal for den samme person<\/h2><\/header>\n<p class=\"le-result-intro\">&ldquo;Jeg er en 32-\u00e5rig mand, 78 kg, 180 cm, jeg vil tabe mig, hvor mange kalorier om dagen?&rdquo; Sp\u00f8rgsm\u00e5let, som millioner af mennesker stiller det.<\/p>\n<div class=\"le-chart-controls\" data-controls=\"simple\" hidden=\"\"><div aria-label=\"Profiler, simpel prompt\" class=\"le-profile-buttons\" role=\"group\"><button aria-controls=\"le-simple-p1\" aria-label=\"P1 \u00b7 Homme 32 ans, 78 kg, 180 cm, 12 % MG, 12 000 pas, 4 muscu\/sem\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"1\" type=\"button\">P1<\/button><button aria-controls=\"le-simple-p2\" aria-label=\"P2 \u00b7 Homme 32 ans, 78 kg, 180 cm, 28 % MG, 4 000 pas, aucun sport\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"2\" type=\"button\">P2<\/button><button aria-controls=\"le-simple-p3\" aria-label=\"P3 \u00b7 Femme 28 ans, 62 kg, 165 cm, 22 % MG, 9 000 pas, 3 fitness\/sem\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"3\" type=\"button\">P3<\/button><button aria-controls=\"le-simple-p4\" aria-label=\"P4 \u00b7 Femme 45 ans, 70 kg, 165 cm, 35 % MG, 3 500 pas, aucun sport\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"4\" type=\"button\">P4<\/button><button aria-controls=\"le-simple-p5\" aria-label=\"P5 \u00b7 Homme 50 ans, 95 kg, 178 cm, 30 % MG, 6 000 pas, 2 marches\/sem\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"5\" type=\"button\">P5<\/button><button aria-controls=\"le-simple-p6\" aria-label=\"P6 \u00b7 Femme 24 ans, 55 kg, 170 cm, 18 % MG, 14 000 pas, 5 courses\/sem\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"6\" type=\"button\">P6<\/button><\/div><button aria-pressed=\"false\" class=\"le-all-button\" data-all=\"\" type=\"button\">Vis alt<\/button><\/div><div class=\"le-figures\" data-charts=\"simple\"><figure aria-labelledby=\"le-simple-p1-title\" class=\"le-chart\" data-profile=\"1\" id=\"le-simple-p1\"><h3 class=\"le-profile-title\" id=\"le-simple-p1-title\"><span class=\"le-profile-code\">P1<\/span> \u00b7 <span class=\"le-profile-description\">Mand 32 \u00e5r, 78 kg, 180 cm, 12 % kropsfedt, 12.000 skridt, 4 styrketr\u00e6ninger\/uge<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"25.0\" data-width=\"60.0\" style=\"--start:25.0%;--span:60.0%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">1.500 til 2.700<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"25.0\" data-width=\"47.5\" style=\"--start:25.0%;--span:47.5%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">1.500 til 2.450<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"52.5\" style=\"--start:30.0%;--span:52.5%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 2.650<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.1 Pro<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"55.0\" style=\"--start:30.0%;--span:55.0%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 2.700<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"25.0\" data-width=\"55.0\" style=\"--start:25.0%;--span:55.0%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">1.500 til 2.600<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.500 til 2.700 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">1.200 kcal forskel<\/strong> (28 svar). Sort linje: m\u00e5l opn\u00e5et komponent for komponent p\u00e5 de m\u00e5lte data (2.360 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-simple-p2-title\" class=\"le-chart\" data-profile=\"2\" id=\"le-simple-p2\"><h3 class=\"le-profile-title\" id=\"le-simple-p2-title\"><span class=\"le-profile-code\">P2<\/span> \u00b7 <span class=\"le-profile-description\">Mand 32 \u00e5r, 78 kg, 180 cm, 28 % kropsfedt, 4.000 skridt, ingen sport<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"55.0\" style=\"--start:30.0%;--span:55.0%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 2.700<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"58.0\" style=\"--start:30.0%;--span:58.0%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 2.760<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"50.0\" style=\"--start:30.0%;--span:50.0%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 2.600<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.1 Pro<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"55.0\" style=\"--start:30.0%;--span:55.0%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 2.700<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"25.0\" data-width=\"50.0\" style=\"--start:25.0%;--span:50.0%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.500 til 2.500<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.500 til 2.760 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">1.260 kcal forskel<\/strong> (28 svar). Sort linje: m\u00e5l opn\u00e5et komponent for komponent p\u00e5 de m\u00e5lte data (1.390 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-simple-p3-title\" class=\"le-chart\" data-profile=\"3\" id=\"le-simple-p3\"><h3 class=\"le-profile-title\" id=\"le-simple-p3-title\"><span class=\"le-profile-code\">P3<\/span> \u00b7 <span class=\"le-profile-description\">Kvinde 28 \u00e5r, 62 kg, 165 cm, 22 % kropsfedt, 9.000 skridt, 3 fitness\/uge<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"10.0\" data-width=\"40.0\" style=\"--start:10.0%;--span:40.0%\"><\/div><span class=\"le-target\" data-target=\"24.9\" style=\"--target:24.9%\"><\/span><\/div><span class=\"le-range-value\">1.200 til 2.000<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"6.5\" data-width=\"34.5\" style=\"--start:6.5%;--span:34.5%\"><\/div><span class=\"le-target\" data-target=\"24.9\" style=\"--target:24.9%\"><\/span><\/div><span class=\"le-range-value\">1.130 til 1.820<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"15.0\" data-width=\"22.5\" style=\"--start:15.0%;--span:22.5%\"><\/div><span class=\"le-target\" data-target=\"24.9\" style=\"--target:24.9%\"><\/span><\/div><span class=\"le-range-value\">1.300 til 1.750<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.1 Pro<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"10.0\" data-width=\"30.0\" style=\"--start:10.0%;--span:30.0%\"><\/div><span class=\"le-target\" data-target=\"24.9\" style=\"--target:24.9%\"><\/span><\/div><span class=\"le-range-value\">1.200 til 1.800<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"10.0\" data-width=\"35.0\" style=\"--start:10.0%;--span:35.0%\"><\/div><span class=\"le-target\" data-target=\"24.9\" style=\"--target:24.9%\"><\/span><\/div><span class=\"le-range-value\">1.200 til 1.900<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.130 til 2.000 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">870 kcal forskel<\/strong> (25 svar). Sort linje: m\u00e5l beregnet komponent for komponent ud fra de m\u00e5lte data (1.499 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-simple-p4-title\" class=\"le-chart\" data-profile=\"4\" id=\"le-simple-p4\"><h3 class=\"le-profile-title\" id=\"le-simple-p4-title\"><span class=\"le-profile-code\">P4<\/span> \u00b7 <span class=\"le-profile-description\">Kvinde 45 \u00e5r, 70 kg, 165 cm, 35 % kropsfedt, 3.500 skridt, ingen sport<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"10.0\" data-width=\"40.0\" style=\"--start:10.0%;--span:40.0%\"><\/div><span class=\"le-target\" data-target=\"4.1\" style=\"--target:4.1%\"><\/span><\/div><span class=\"le-range-value\">1.200 til 2.000<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"5.0\" data-width=\"37.5\" style=\"--start:5.0%;--span:37.5%\"><\/div><span class=\"le-target\" data-target=\"4.1\" style=\"--target:4.1%\"><\/span><\/div><span class=\"le-range-value\">1.100 til 1.850<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"12.5\" data-width=\"30.0\" style=\"--start:12.5%;--span:30.0%\"><\/div><span class=\"le-target\" data-target=\"4.1\" style=\"--target:4.1%\"><\/span><\/div><span class=\"le-range-value\">1.250 til 1.850<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"10.0\" data-width=\"30.0\" style=\"--start:10.0%;--span:30.0%\"><\/div><span class=\"le-target\" data-target=\"4.1\" style=\"--target:4.1%\"><\/span><\/div><span class=\"le-range-value\">1.200 til 1.800<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.100 til 2.000 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">900 kcal forskel<\/strong> (22 svar). Sort linje: m\u00e5l beregnet komponent for komponent ud fra de m\u00e5lte data (1.082 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-simple-p5-title\" class=\"le-chart\" data-profile=\"5\" id=\"le-simple-p5\"><h3 class=\"le-profile-title\" id=\"le-simple-p5-title\"><span class=\"le-profile-code\">P5<\/span> \u00b7 <span class=\"le-profile-description\">Mand 50 \u00e5r, 95 kg, 178 cm, 30 % kropsfedt, 6.000 skridt, 2 g\u00e5ture\/uge<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"25.0\" data-width=\"45.0\" style=\"--start:25.0%;--span:45.0%\"><\/div><span class=\"le-target\" data-target=\"45.9\" style=\"--target:45.9%\"><\/span><\/div><span class=\"le-range-value\">1.500 til 2.400<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"34.0\" data-width=\"43.5\" style=\"--start:34.0%;--span:43.5%\"><\/div><span class=\"le-target\" data-target=\"45.9\" style=\"--target:45.9%\"><\/span><\/div><span class=\"le-range-value\">1.680 til 2.550<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"32.5\" data-width=\"32.5\" style=\"--start:32.5%;--span:32.5%\"><\/div><span class=\"le-target\" data-target=\"45.9\" style=\"--target:45.9%\"><\/span><\/div><span class=\"le-range-value\">1.650 til 2.300<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"25.0\" data-width=\"40.0\" style=\"--start:25.0%;--span:40.0%\"><\/div><span class=\"le-target\" data-target=\"45.9\" style=\"--target:45.9%\"><\/span><\/div><span class=\"le-range-value\">1.500 til 2.300<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.500 til 2.550 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">1.050 kcal forskel<\/strong> (22 svar). Sort linje: m\u00e5l beregnet komponent for komponent ud fra de m\u00e5lte data (1.918 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-simple-p6-title\" class=\"le-chart\" data-profile=\"6\" id=\"le-simple-p6\"><h3 class=\"le-profile-title\" id=\"le-simple-p6-title\"><span class=\"le-profile-code\">P6<\/span> \u00b7 <span class=\"le-profile-description\">Kvinde 24 \u00e5r, 55 kg, 170 cm, 18 % kropsfedt, 14.000 skridt, 5 l\u00f8b\/uge<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"10.0\" data-width=\"35.0\" style=\"--start:10.0%;--span:35.0%\"><\/div><span class=\"le-target\" data-target=\"36.8\" style=\"--target:36.8%\"><\/span><\/div><span class=\"le-range-value\">1.200 til 1.900<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"10.0\" data-width=\"32.5\" style=\"--start:10.0%;--span:32.5%\"><\/div><span class=\"le-target\" data-target=\"36.8\" style=\"--target:36.8%\"><\/span><\/div><span class=\"le-range-value\">1.200 til 1.850<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"30.0\" style=\"--start:30.0%;--span:30.0%\"><\/div><span class=\"le-target\" data-target=\"36.8\" style=\"--target:36.8%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 2.200<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.200 til 2.200 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">1.000 kcal forskel<\/strong> (16 svar). Sort linje: m\u00e5l beregnet komponent for komponent ud fra de m\u00e5lte data (1.735 kcal).<\/figcaption>\n<\/figure>\n<\/div><div class=\"le-behavior\"><h3 class=\"le-behavior-title\">AI-adf\u00e6rd, simpel prompt (147 svar)<\/h3><ul class=\"le-behavior-list\"><li data-percent=\"0\" style=\"--percent:0%\"><strong>0 %<\/strong><span>sp\u00f8rger om kropsfedtprocent<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<li data-percent=\"1\" style=\"--percent:1%\"><strong>1 %<\/strong><span>sp\u00f8rger om det daglige skridttal<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<li data-percent=\"97\" style=\"--percent:97%\"><strong>97 %<\/strong><span>bruger et deklarativt aktivitetsgitter<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<li data-percent=\"48\" style=\"--percent:48%\"><strong>48 %<\/strong><span>citerer Mifflin-St Jeor eller Harris-Benedict (1990, 1919)<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<li data-percent=\"0\" style=\"--percent:0%\"><strong>0 %<\/strong><span>n\u00e6vner f\u00f8devarers termiske effekt<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<\/ul>\n<\/div><div class=\"le-insight\">P1 og P2 stillede <strong>pr\u00e6cis det samme sp\u00f8rgsm\u00e5l<\/strong> (samme alder, v\u00e6gt, h\u00f8jde) og fik det samme gitter. Deres reelle forbrug adskiller sig dog med n\u00e6sten 1.000 kcal om dagen: 12 % kropsfedt og 12.000 skridt p\u00e5 den ene side, 28 % og 4.000 skridt p\u00e5 den anden.<\/div><\/section>\n<section aria-labelledby=\"le-complet-title\" class=\"le-section le-complet\" id=\"le-complet\"><header class=\"le-section-heading\"><span class=\"le-section-label\">03 \u00b7 Resultat 2<\/span><h2 id=\"le-complet-title\">Fuld prompt: stadig et hul p\u00e5 650 kcal<\/h2><\/header>\n<p class=\"le-result-intro\">Vi giver alt: kropsfedt, skridt pr. dag, sessioner, og &ldquo;giv mig et pr\u00e6cist tal&rdquo;. Alle adlyder. Et pr\u00e6cist tal er ikke et korrekt tal.<\/p>\n<div class=\"le-chart-controls\" data-controls=\"complet\" hidden=\"\"><div aria-label=\"Profiler, fuld prompt\" class=\"le-profile-buttons\" role=\"group\"><button aria-controls=\"le-complet-p1\" aria-label=\"P1 \u00b7 Homme 32 ans, 78 kg, 180 cm, 12 % MG, 12 000 pas, 4 muscu\/sem\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"1\" type=\"button\">P1<\/button><button aria-controls=\"le-complet-p2\" aria-label=\"P2 \u00b7 Homme 32 ans, 78 kg, 180 cm, 28 % MG, 4 000 pas, aucun sport\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"2\" type=\"button\">P2<\/button><button aria-controls=\"le-complet-p3\" aria-label=\"P3 \u00b7 Femme 28 ans, 62 kg, 165 cm, 22 % MG, 9 000 pas, 3 fitness\/sem\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"3\" type=\"button\">P3<\/button><button aria-controls=\"le-complet-p4\" aria-label=\"P4 \u00b7 Femme 45 ans, 70 kg, 165 cm, 35 % MG, 3 500 pas, aucun sport\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"4\" type=\"button\">P4<\/button><button aria-controls=\"le-complet-p5\" aria-label=\"P5 \u00b7 Homme 50 ans, 95 kg, 178 cm, 30 % MG, 6 000 pas, 2 marches\/sem\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"5\" type=\"button\">P5<\/button><button aria-controls=\"le-complet-p6\" aria-label=\"P6 \u00b7 Femme 24 ans, 55 kg, 170 cm, 18 % MG, 14 000 pas, 5 courses\/sem\" aria-pressed=\"false\" class=\"le-profile-button\" data-profile=\"6\" type=\"button\">P6<\/button><\/div><button aria-pressed=\"false\" class=\"le-all-button\" data-all=\"\" type=\"button\">Vis alt<\/button><\/div><div class=\"le-figures\" data-charts=\"complet\"><figure aria-labelledby=\"le-complet-p1-title\" class=\"le-chart\" data-profile=\"1\" id=\"le-complet-p1\"><h3 class=\"le-profile-title\" id=\"le-complet-p1-title\"><span class=\"le-profile-code\">P1<\/span> \u00b7 <span class=\"le-profile-description\">Mand 32 \u00e5r, 78 kg, 180 cm, 12 % kropsfedt, 12.000 skridt, 4 styrketr\u00e6ninger\/uge<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"67.5\" data-width=\"20.0\" style=\"--start:67.5%;--span:20.0%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">2.350 til 2.750<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"65.0\" data-width=\"10.0\" style=\"--start:65.0%;--span:10.0%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">2.300 til 2.500<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"55.0\" data-width=\"15.0\" style=\"--start:55.0%;--span:15.0%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">2.100 til 2.400<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.1 Pro<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"65.0\" data-width=\"20.0\" style=\"--start:65.0%;--span:20.0%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">2.300 til 2.700<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"62.5\" data-width=\"10.0\" style=\"--start:62.5%;--span:10.0%\"><\/div><span class=\"le-target\" data-target=\"68.0\" style=\"--target:68.0%\"><\/span><\/div><span class=\"le-range-value\">2.250 til 2.450<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">2.100 til 2.750 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">650 kcal&rsquo;s sp\u00e6nd<\/strong> (28 svar). Sort linje: m\u00e5l opn\u00e5et komponent for komponent p\u00e5 de m\u00e5lte data (2.360 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-complet-p2-title\" class=\"le-chart\" data-profile=\"2\" id=\"le-complet-p2\"><h3 class=\"le-profile-title\" id=\"le-complet-p2-title\"><span class=\"le-profile-code\">P2<\/span> \u00b7 <span class=\"le-profile-description\">Mand 32 \u00e5r, 78 kg, 180 cm, 28 % kropsfedt, 4.000 skridt, ingen sport<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"10.0\" style=\"--start:30.0%;--span:10.0%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 1.800<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"37.5\" data-width=\"12.5\" style=\"--start:37.5%;--span:12.5%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.750 til 2.000<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"27.5\" data-width=\"10.0\" style=\"--start:27.5%;--span:10.0%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.550 til 1.750<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.1 Pro<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"20.0\" data-width=\"20.0\" style=\"--start:20.0%;--span:20.0%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.400 til 1.800<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"32.5\" data-width=\"15.0\" style=\"--start:32.5%;--span:15.0%\"><\/div><span class=\"le-target\" data-target=\"19.5\" style=\"--target:19.5%\"><\/span><\/div><span class=\"le-range-value\">1.650 til 1.950<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.400 til 2.000 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">600 kcal&rsquo;s sp\u00e6nd<\/strong> (28 svar). Sort linje: m\u00e5l opn\u00e5et komponent for komponent p\u00e5 de m\u00e5lte data (1.390 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-complet-p3-title\" class=\"le-chart\" data-profile=\"3\" id=\"le-complet-p3\"><h3 class=\"le-profile-title\" id=\"le-complet-p3-title\"><span class=\"le-profile-code\">P3<\/span> \u00b7 <span class=\"le-profile-description\">Kvinde 28 \u00e5r, 62 kg, 165 cm, 22 % kropsfedt, 9.000 skridt, 3 fitness\/uge<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"12.5\" style=\"--start:30.0%;--span:12.5%\"><\/div><span class=\"le-target\" data-target=\"24.9\" style=\"--target:24.9%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 1.850<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"35.0\" data-width=\"7.5\" style=\"--start:35.0%;--span:7.5%\"><\/div><span class=\"le-target\" data-target=\"24.9\" style=\"--target:24.9%\"><\/span><\/div><span class=\"le-range-value\">1.700 til 1.850<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"25.0\" data-width=\"12.5\" style=\"--start:25.0%;--span:12.5%\"><\/div><span class=\"le-target\" data-target=\"24.9\" style=\"--target:24.9%\"><\/span><\/div><span class=\"le-range-value\">1.500 til 1.750<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"22.5\" data-width=\"22.5\" style=\"--start:22.5%;--span:22.5%\"><\/div><span class=\"le-target\" data-target=\"24.9\" style=\"--target:24.9%\"><\/span><\/div><span class=\"le-range-value\">1.450 til 1.900<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.450 til 1.900 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">450 kcal&rsquo;s sp\u00e6nd<\/strong> (22 svar). Sort linje: m\u00e5l beregnet komponent for komponent p\u00e5 de m\u00e5lte data (1.499 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-complet-p4-title\" class=\"le-chart\" data-profile=\"4\" id=\"le-complet-p4\"><h3 class=\"le-profile-title\" id=\"le-complet-p4-title\"><span class=\"le-profile-code\">P4<\/span> \u00b7 <span class=\"le-profile-description\">Kvinde 45 \u00e5r, 70 kg, 165 cm, 35 % kropsfedt, 3.500 skridt, ingen sport<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"10.0\" data-width=\"12.5\" style=\"--start:10.0%;--span:12.5%\"><\/div><span class=\"le-target\" data-target=\"4.1\" style=\"--target:4.1%\"><\/span><\/div><span class=\"le-range-value\">1.200 til 1.450<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"12.5\" data-width=\"12.5\" style=\"--start:12.5%;--span:12.5%\"><\/div><span class=\"le-target\" data-target=\"4.1\" style=\"--target:4.1%\"><\/span><\/div><span class=\"le-range-value\">1.250 til 1.500<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"15.0\" data-width=\"5.0\" style=\"--start:15.0%;--span:5.0%\"><\/div><span class=\"le-target\" data-target=\"4.1\" style=\"--target:4.1%\"><\/span><\/div><span class=\"le-range-value\">1.300 til 1.400<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"10.0\" data-width=\"20.0\" style=\"--start:10.0%;--span:20.0%\"><\/div><span class=\"le-target\" data-target=\"4.1\" style=\"--target:4.1%\"><\/span><\/div><span class=\"le-range-value\">1.200 til 1.600<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.200 til 1.600 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">400 kcal forskel<\/strong> (22 svar). Sort linje: m\u00e5l beregnet komponent for komponent ud fra de m\u00e5lte data (1.082 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-complet-p5-title\" class=\"le-chart\" data-profile=\"5\" id=\"le-complet-p5\"><h3 class=\"le-profile-title\" id=\"le-complet-p5-title\"><span class=\"le-profile-code\">P5<\/span> \u00b7 <span class=\"le-profile-description\">Mand 50 \u00e5r, 95 kg, 178 cm, 30 % kropsfedt, 6.000 skridt, 2 g\u00e5ture\/uge<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"42.5\" data-width=\"17.5\" style=\"--start:42.5%;--span:17.5%\"><\/div><span class=\"le-target\" data-target=\"45.9\" style=\"--target:45.9%\"><\/span><\/div><span class=\"le-range-value\">1.850 til 2.200<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"45.0\" data-width=\"7.5\" style=\"--start:45.0%;--span:7.5%\"><\/div><span class=\"le-target\" data-target=\"45.9\" style=\"--target:45.9%\"><\/span><\/div><span class=\"le-range-value\">1.900 til 2.050<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"42.5\" data-width=\"6.5\" style=\"--start:42.5%;--span:6.5%\"><\/div><span class=\"le-target\" data-target=\"45.9\" style=\"--target:45.9%\"><\/span><\/div><span class=\"le-range-value\">1.850 til 1.980<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"30.0\" data-width=\"25.0\" style=\"--start:30.0%;--span:25.0%\"><\/div><span class=\"le-target\" data-target=\"45.9\" style=\"--target:45.9%\"><\/span><\/div><span class=\"le-range-value\">1.600 til 2.100<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.600 til 2.200 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">600 kcal&rsquo;s sp\u00e6nd<\/strong> (22 svar). Sort linje: m\u00e5l beregnet komponent for komponent ud fra de m\u00e5lte data (1.918 kcal).<\/figcaption>\n<\/figure>\n<figure aria-labelledby=\"le-complet-p6-title\" class=\"le-chart\" data-profile=\"6\" id=\"le-complet-p6\"><h3 class=\"le-profile-title\" id=\"le-complet-p6-title\"><span class=\"le-profile-code\">P6<\/span> \u00b7 <span class=\"le-profile-description\">Kvinde 24 \u00e5r, 55 kg, 170 cm, 18 % kropsfedt, 14.000 skridt, 5 l\u00f8b\/uge<\/span><\/h3><div class=\"le-chart-body\"><div class=\"le-axis\"><span>1000 kcal<\/span><span>3000 kcal<\/span><div aria-hidden=\"true\" class=\"le-axis-marks\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.5)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"45.0\" data-width=\"20.0\" style=\"--start:45.0%;--span:20.0%\"><\/div><span class=\"le-target\" data-target=\"36.8\" style=\"--target:36.8%\"><\/span><\/div><span class=\"le-range-value\">1.900 til 2.300<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">ChatGPT (GPT-5.4 mini)<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"42.5\" data-width=\"17.5\" style=\"--start:42.5%;--span:17.5%\"><\/div><span class=\"le-target\" data-target=\"36.8\" style=\"--target:36.8%\"><\/span><\/div><span class=\"le-range-value\">1.850 til 2.200<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Gemini 3.7 Flash<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"65.0\" data-width=\"10.0\" style=\"--start:65.0%;--span:10.0%\"><\/div><span class=\"le-target\" data-target=\"36.8\" style=\"--target:36.8%\"><\/span><\/div><span class=\"le-range-value\">2.300 til 2.500<\/span><\/div><div class=\"le-chart-row\"><span class=\"le-model\">Claude Opus<\/span><div aria-hidden=\"true\" class=\"le-track\"><div class=\"le-range\" data-start=\"45.0\" data-width=\"25.0\" style=\"--start:45.0%;--span:25.0%\"><\/div><span class=\"le-target\" data-target=\"36.8\" style=\"--target:36.8%\"><\/span><\/div><span class=\"le-range-value\">1.900 til 2.400<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Alle IA\u2019er tilsammen: <strong class=\"le-caption-range\">1.850 til 2.500 kcal<\/strong>, dvs. <strong class=\"le-caption-gap\">650 kcal&rsquo;s sp\u00e6nd<\/strong> (19 svar). Sort linje: m\u00e5l beregnet komponent for komponent ud fra m\u00e5lte data (1.735 kcal).<\/figcaption>\n<\/figure>\n<\/div><div class=\"le-behavior\"><h3 class=\"le-behavior-title\">AI-adf\u00e6rd, fuld prompt (144 svar)<\/h3><ul class=\"le-behavior-list\"><li data-percent=\"40\" style=\"--percent:40%\"><strong>40 %<\/strong><span>faktisk bruger det oplyste kropsfedt<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<li data-percent=\"42\" style=\"--percent:42%\"><strong>42 %<\/strong><span>omregner de angivne skridt til kalorier<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<li data-percent=\"14\" style=\"--percent:14%\"><strong>14 %<\/strong><span>n\u00e6vner metabolisk tilpasning<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<li data-percent=\"3\" style=\"--percent:3%\"><strong>3 %<\/strong><span>n\u00e6vner f\u00f8devarers termiske effekt<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<li data-percent=\"97\" style=\"--percent:97%\"><strong>97 %<\/strong><span>giver et enkelt tal, som \u00f8nsket<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<\/ul>\n<\/div><div class=\"le-comparison\" data-comparison=\"\"><h3 class=\"le-comparison-title\">P1 mod P2-testen: samme v\u00e6gt, forskellige kroppe<\/h3><ul class=\"le-comparison-stats\"><li><strong>699 <small>kcal<\/small><\/strong><span>af forskel mellem P1 og P2 if\u00f8lge AI'erne (gennemsnit)<\/span><\/li>\n<li><strong>970 <small>kcal<\/small><\/strong><span>af forskel n\u00e5r man beregner komponent for komponent<\/span><\/li>\n<li><strong>+324 <small>kcal<\/small><\/strong><span>for meget for den stillesiddende profil ved 28 % kropsfedt<\/span><\/li>\n<\/ul>\n<\/div><div class=\"le-insight\">AI'erne ser forskellen mellem de to m\u00e6nd, men undervurderer den: de justerer en populationsformel i stedet for at m\u00e5le. Den stillesiddende profil, den der \u00abg\u00f8r alting rigtigt\u00bb, f\u00e5r et m\u00e5l, der er for h\u00f8jt, og taber intet.<\/div><\/section>\n<section aria-labelledby=\"le-suivi-title\" class=\"le-section le-suivi\" id=\"le-suivi\"><div class=\"le-suivi-inner\"><header class=\"le-section-heading\"><span class=\"le-section-label\">04 \u00b7 Det egentlige sp\u00f8rgsm\u00e5l<\/span><h2 id=\"le-suivi-title\">Problemet er ikke dag 1, det er <span class=\"le-time-headline\">89 f\u00f8lgende dage<\/span><\/h2><\/header>\n<p class=\"le-time-intro\">78 % af de detaljerede svar r\u00e5der til at \u00abveje sig og justere\u00bb. Ingen g\u00f8r det for dig.<\/p>\n<div class=\"le-time-stage\"><div aria-hidden=\"true\" class=\"le-time-dial\" data-visual-copy=\"\"><div class=\"le-dial-face\"><span class=\"le-dial-unit\" data-current-unit=\"\">Dag<\/span><span class=\"le-dial-day\" data-current-day=\"\">1<\/span><\/div><span class=\"le-dial-caption\">Tallet er fastl\u00e5st p\u00e5 dag 1.<\/span><\/div><ul class=\"le-timeline\"><li><strong><span>Dag<\/span> <b>1<\/b><\/strong><span>Chatbotten modtager en v\u00e6gt og svarer \u00e9n gang.<\/span><\/li>\n<li><strong><span>Dag<\/span> <b>2<\/b><\/strong><span>Du gik 4.000 skridt i stedet for 11.000. Det ved den ikke.<\/span><\/li>\n<li><strong><span>Uge<\/span> <b>3<\/b><\/strong><span>Du tr\u00e6nede 6 gange og \u00e6ndrede dine makroer. Det ved den ikke.<\/span><\/li>\n<li><strong><span>Dag<\/span> <b>90<\/b><\/strong><span>Du tabte 4 kg, dit stofskifte faldt og tilpassede sig derefter. Det ved den stadig ikke.<\/span><\/li>\n<\/ul>\n<\/div><div class=\"le-checklists\"><div class=\"le-checklist le-checklist-no\"><h3>Det chatbotten ikke ved<\/h3><ul><li><span>\u2715<\/span><span>Dine skridt i dag<\/span><\/li>\n<li><span>\u2715<\/span><span>Dine m\u00e5ltider i dag og deres termiske effekt<\/span><\/li>\n<li><span>\u2715<\/span><span>Dit reelle kropsfedt og dets udvikling<\/span><\/li>\n<li><span>\u2715<\/span><span>Din stofskiftes tilpasning over ugerne<\/span><\/li>\n<li><span>\u2715<\/span><span>Ingen kurve, intet diagram over dit forbrug<\/span><\/li>\n<\/ul>\n<\/div><div class=\"le-checklist le-checklist-yes\"><h3>Hvad \u00e6gte tracking kr\u00e6ver<\/h3><ul><li><span>\u2713<\/span><span>Forbrug genberegnet hver dag ud fra m\u00e5linger<\/span><\/li>\n<li><span>\u2713<\/span><span>M\u00e5l der bev\u00e6ger sig med skridt og tr\u00e6ningspas<\/span><\/li>\n<li><span>\u2713<\/span><span>Kropsfedt m\u00e5lt igen regelm\u00e6ssigt<\/span><\/li>\n<li><span>\u2713<\/span><span>Automatisk korrektion af metabolisk tilpasning<\/span><\/li>\n<li><span>\u2713<\/span><span>En l\u00e6sbar kurve over din TDEE og dens udvikling<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><div class=\"le-verdict\"><strong>Konklusion: virker det at tabe sig med ChatGPT?<\/strong> Ved held, nogle gange. Ved metode, nej: uden m\u00e5ling eller daglige opdateringer forbliver svaret et populationsestimat, fastfrosset den f\u00f8rste dag. Testen kan laves om p\u00e5 fem minutter med din egen profil.<\/div><\/section>\n<section aria-labelledby=\"le-app-title\" class=\"le-section le-app\" id=\"le-app\"><header class=\"le-section-heading\"><span class=\"le-section-label\">05 \u00b7 Og Lean?<\/span><h2 id=\"le-app-title\">AI'en der m\u00e5ler over for AI'en der g\u00e6tter<\/h2><\/header>\n<p class=\"le-app-intro\">Lean bruger ogs\u00e5 AI, men til at m\u00e5le: BodyScan til kropsfedt, fotoscan til tallerkenen, skridtt\u00e6ller til skridt. Derefter genberegner den hver dag de fem komponenter i dit forbrug og tegner kurven.<\/p>\n<div class=\"le-app-panel\"><div class=\"le-feature-list\"><span class=\"le-feature le-feature-0\">BMR p\u00e5 m\u00e5lt fedtfri masse<\/span><span class=\"le-feature le-feature-1\">NEAT p\u00e5 reelle skridt<\/span><span class=\"le-feature le-feature-2\">EAT pr. session<\/span><span class=\"le-feature le-feature-3\">TEF ud fra makroer<\/span><span class=\"le-feature le-feature-4\">Metabolisk tilpasning<\/span><\/div><strong>Lean m\u00e5ler, genberegner og f\u00f8lger med, hver dag<\/strong><span>F\u00f8rste app til at beregne metabolisk tilpasning. Gratis download, 7 dages pr\u00f8veperiode p\u00e5 \u00e5rsabonnementet. 4,7\/5 p\u00e5 App Store, mere end 10.000 brugere.<\/span><p class=\"le-store-links\"><a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&amp;utm_medium=etude&amp;utm_campaign=chatgpt-calories\" rel=\"noopener\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger Lean sur l\\'App Store\" width=\"150\" height=\"50\" style=\"height:50px;width:auto;display:block;\"><\/a><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&amp;utm_source=seo&amp;utm_medium=etude&amp;utm_campaign=chatgpt-calories\" rel=\"noopener\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"T\u00e9l\u00e9charger Lean sur Google Play\" width=\"168\" height=\"50\" style=\"height:50px;width:auto;display:block;\"><\/a><\/p>\n<\/div><\/section>\n<section aria-labelledby=\"le-donnees-title\" class=\"le-section le-donnees\" id=\"le-donnees\"><header class=\"le-section-heading\"><span class=\"le-section-label\">Data<\/span><h2 id=\"le-donnees-title\">Dataene, profil for profil<\/h2><\/header>\n<ul class=\"le-data-list\"><li class=\"le-data-record\" id=\"le-data-p1\"><h3 class=\"le-data-heading\"><strong>P1<\/strong> \u00b7 Mand 32 \u00e5r, 78 kg, 180 cm, 12 % kropsfedt, 12.000 skridt, 4 styrkepas\/uge<\/h3><div class=\"le-data-values\">Simpel prompt: <strong>1.500 til 2.700 kcal<\/strong> (28 svar) \u00b7 Fuld prompt: <strong>2.100 til 2.750 kcal<\/strong> (28 svar) \u00b7 Komponent for komponent-m\u00e5l: <strong>2.360 kcal<\/strong> (BMR 1.853, NEAT 504, EAT 267, TEF 236, TDEE 2.860)<\/div><\/li>\n<li class=\"le-data-record\" id=\"le-data-p2\"><h3 class=\"le-data-heading\"><strong>P2<\/strong> \u00b7 Mand 32 \u00e5r, 78 kg, 180 cm, 28 % kropsfedt, 4.000 skridt, ingen sport<\/h3><div class=\"le-data-values\">Simpel prompt: <strong>1.500 til 2.760 kcal<\/strong> (28 svar) \u00b7 Fuld prompt: <strong>1.400 til 2.000 kcal<\/strong> (28 svar) \u00b7 Komponent for komponent-m\u00e5l: <strong>1.390 kcal<\/strong> (BMR 1.583, NEAT 168, EAT 0, TEF 139, TDEE 1.890)<\/div><\/li>\n<li class=\"le-data-record\" id=\"le-data-p3\"><h3 class=\"le-data-heading\"><strong>P3<\/strong> \u00b7 Kvinde 28 \u00e5r, 62 kg, 165 cm, 22 % kropsfedt, 9.000 skridt, 3 fitnesspas\/uge<\/h3><div class=\"le-data-values\">Simpel prompt: <strong>1.130 til 2.000 kcal<\/strong> (25 svar) \u00b7 Fuld prompt: <strong>1.450 til 1.900 kcal<\/strong> (22 svar) \u00b7 Komponent for komponent-m\u00e5l: <strong>1.499 kcal<\/strong> (BMR 1.415, NEAT 275, EAT 159, TEF 150, TDEE 1.999)<\/div><\/li>\n<li class=\"le-data-record\" id=\"le-data-p4\"><h3 class=\"le-data-heading\"><strong>P4<\/strong> \u00b7 Kvinde 45 \u00e5r, 70 kg, 165 cm, 35 % kropsfedt, 3.500 skridt, ingen sport<\/h3><div class=\"le-data-values\">Simpel prompt: <strong>1.100 til 2.000 kcal<\/strong> (22 svar) \u00b7 Fuld prompt: <strong>1.200 til 1.600 kcal<\/strong> (22 svar) \u00b7 Komponent for komponent-m\u00e5l: <strong>1.082 kcal<\/strong> (BMR 1.353, NEAT 121, EAT 0, TEF 108, TDEE 1.582)<\/div><\/li>\n<li class=\"le-data-record\" id=\"le-data-p5\"><h3 class=\"le-data-heading\"><strong>P5<\/strong> \u00b7 Mand 50 \u00e5r, 95 kg, 178 cm, 30 % kropsfedt, 6.000 skridt, 2 g\u00e5ture\/uge<\/h3><div class=\"le-data-values\">Simpel prompt: <strong>1.500 til 2.550 kcal<\/strong> (22 svar) \u00b7 Fuld prompt: <strong>1.600 til 2.200 kcal<\/strong> (22 svar) \u00b7 Komponent for komponent-m\u00e5l: <strong>1.918 kcal<\/strong> (BMR 1.806, NEAT 303, EAT 117, TEF 192, TDEE 2.418)<\/div><\/li>\n<li class=\"le-data-record\" id=\"le-data-p6\"><h3 class=\"le-data-heading\"><strong>P6<\/strong> \u00b7 Kvinde 24 \u00e5r, 55 kg, 170 cm, 18 % kropsfedt, 14.000 skridt, 5 l\u00f8b\/uge<\/h3><div class=\"le-data-values\">Simpel prompt: <strong>1.200 til 2.200 kcal<\/strong> (16 svar) \u00b7 Fuld prompt: <strong>1.850 til 2.500 kcal<\/strong> (19 svar) \u00b7 Komponent for komponent-m\u00e5l: <strong>1.735 kcal<\/strong> (BMR 1.344, NEAT 391, EAT 326, TEF 174, TDEE 2.235)<\/div><\/li>\n<\/ul>\n<p class=\"le-data-note\">Variabilitet hos den samme IA p\u00e5 den samme gentagne prompt (fuld prompt, gennemsnitlig forskel mellem gentagelser): Claude Opus 73 kcal, Gemini 3.1 Pro 175 kcal, Gemini 3.7 Flash 57 kcal, ChatGPT (GPT-5.4 mini) 98 kcal, ChatGPT (GPT-5.5) 96 kcal.<\/p>\n<p class=\"le-data-note\">Fuld datas\u00e6t (prompts, 291 r\u00e5 svar, udtr\u00e6k, scripts): <a href=\"https:\/\/doi.org\/10.5281\/zenodo.22662006\" rel=\"noopener\">Zenodo, DOI 10.5281\/zenodo.22662006<\/a>, CC BY 4.0-licens.<\/p>\n<details class=\"le-disclosure\"><summary>Detaljeret metode og begr\u00e6nsninger<\/summary>\n<p>Modeller forespurgt via API med standardindstillinger og uden systeminstruktion: GPT-5.5 og GPT-5.4 mini (OpenAI), Gemini 3.7 Flash og Gemini 3.1 Pro (Google). Claude Opus (Anthropic) forespurgt via den officielle kommandolinjegr\u00e6nseflade med en neutral systemprompt og uden nogen kontekst. Seks profiler, to promptniveauer, fransk og engelsk, 2 til 3 gentagelser pr. kombination, 291 svar indsamlet den 8. september 2026 (Gemini 3.1 Pro: 27 svar, API-hastighed begr\u00e6nset; andre modeller: 48 til 72).<\/p>\n<p>L\u00e6sning af svarene: en automatisk udtr\u00e6kker (GPT-5.4 mini, temperatur 0, strengt JSON-skema) identificerer det anbefalede indtagsm\u00e5l (min og max n\u00e5r et interval eller en skala er angivet) og adf\u00e6rdene (sp\u00f8rgsm\u00e5l stillet f\u00f8r svar, aktivitetsgrids, faktisk brug af det oplyste kropsfedt og de oplyste skridt, omtale af metabolisk tilpasning og den termiske effekt). Udtr\u00e6kket offentligg\u00f8res sammen med de r\u00e5 svar, linje for linje.<\/p>\n<p>Begr\u00e6nsninger: fiktive profiler; offentlige referenceformler (Katch-McArdle p\u00e5 fedtfri masse, Ainsworth 2011-kompendiet, TEF p\u00e5 10 %) som fungerer som pejlem\u00e6rke, ikke som sandhed i praksis; modellerne udvikler sig, og svarene \u00e6ndrer sig fra uge til uge, hvilket er en del af konstateringen. Lean udgiver denne unders\u00f8gelse og s\u00e6lger en tracking-app: metode og data er \u00e5bne, s\u00e5 alle kan genskabe den.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>Videnskabelige kilder<\/summary>\n<ul><li>Mifflin MD et al. A new predictive equation for resting energy expenditure in healthy individuals. <em>Am J Clin Nutr<\/em>. 1990;51(2):241-7. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/2305711\/\" rel=\"noopener\">PubMed 2305711<\/a><\/li>\n<li>Ainsworth BE et al. 2011 Compendium of Physical Activities. <em>Med Sci Sports Exerc<\/em>. 2011;43(8):1575-81. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/21681120\/\" rel=\"noopener\">PubMed 21681120<\/a><\/li>\n<li>Levine JA et al. Interindividual variation in posture allocation. <em>Videnskab<\/em>. 2005;307(5709):584-6. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/15681386\/\" rel=\"noopener\">PubMed 15681386<\/a><\/li>\n<li>Trexler ET et al. Metabolic adaptation to weight loss: implications for the athlete. <em>J Int Soc Sports Nutr<\/em>. 2014;11:7. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/24571926\/\" rel=\"noopener\">PubMed 24571926<\/a><\/li>\n<li>Westerterp KR. Diet induced thermogenesis. <em>Nutr Metab<\/em>. 2004;1:5. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/15507147\/\" rel=\"noopener\">PubMed 15507147<\/a><\/li>\n<\/ul>\n<\/details>\n<p class=\"le-data-note\">Studie offentliggjort af Lean-teamet. Pressekontakt: franckbarriere@lean-app.com. Ikke medicinsk r\u00e5dgivning.<\/p>\n<\/section>\n<section aria-labelledby=\"le-faq-title\" class=\"le-section le-faq\" id=\"le-faq\"><header class=\"le-section-heading\"><h2 id=\"le-faq-title\">Ofte stillede sp\u00f8rgsm\u00e5l<\/h2><\/header>\n<details class=\"le-disclosure\"><summary>Kan ChatGPT beregne, hvor mange kalorier jeg skal spise?<\/summary>\n<p>Den giver et tal, men ikke en m\u00e5ling. Ud af 291 svar spurgte ingen AI om kropsfedt (kun \u00e9n spurgte om skridttallet), og 97 % af svarene p\u00e5 den simple prompt bygger p\u00e5 en deklarativ aktivitetsgr\u00e6nse (stillesiddende, moderat, aktiv). Resultatet er et statistisk gennemsnit, der ignorerer din kropssammens\u00e6tning og din reelle aktivitet, med op til 1.260 kcal i forskel for den samme person.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>Hvorfor giver AI'er s\u00e5 forskellige tal for den samme profil?<\/summary>\n<p>Fordi de ikke har nogen m\u00e5ling. De anvender en populationsformel (oftest Mifflin-St Jeor 1990) og derefter en aktivitetsmultiplikator valgt p\u00e5 gef\u00fchl. To m\u00e6nd p\u00e5 78 kg, den ene med 12 % kropsfedt og 12.000 skridt, den anden med 28 % og 4.000 skridt, f\u00e5r det samme svar p\u00e5 den simple prompt, selv om deres reelle forbrug adskiller sig med n\u00e6sten 1.000 kcal.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>Hj\u00e6lper det at give ChatGPT flere detaljer?<\/summary>\n<p>Kun delvist. Med kropsfedt, skridt og tr\u00e6ningspas i prompten er forskellen mellem AI'er stadig 650 kcal for den samme profil, kropsfedt bruges faktisk kun i beregningen i 40 % af svarene og skridt i 42 %. Og vigtigst af alt er svaret fastl\u00e5st: den ved ikke, hvor meget du har g\u00e5et eller spist i dag, eller hvordan dit stofskifte tilpasser sig over ugerne.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>Hvad er metabolisk tilpasning, og hvorfor \u00e6ndrer det svaret?<\/summary>\n<p>Ved et langvarigt kalorieunderskud falder basalstofskiftet ud over det, v\u00e6gttabet forklarer. Et tal, der er korrekt i dag, bliver for h\u00f8jt efter et par uger. Kun 14 % af de detaljerede svar n\u00e6vnte det, og ingen beregner det. Det er den hyppigste \u00e5rsag til plateauer.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>Hvordan beregner man korrekt sine kalorier for at tabe sig?<\/summary>\n<p>Ved at opbygge forbruget komponent for komponent, TDEE = BMR + NEAT + EAT + TEF, med basalstofskiftet beregnet ud fra den reelle fedtfri masse, NEAT ud fra m\u00e5lte skridt, EAT ud fra de tr\u00e6ningspas, der faktisk er gennemf\u00f8rt, TEF ud fra de indtagne makroer, og derefter f\u00f8lge udviklingen dag for dag og korrigere, n\u00e5r kroppen tilpasser sig. Det er en opf\u00f8lgning, ikke et svar i \u00e9n s\u00e6tning.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>Er AI ubrugelig til ern\u00e6ring?<\/summary>\n<p>Nej. AI er v\u00e6rdifuld, n\u00e5r den m\u00e5ler: at estimere kropsfedt ud fra et foto, genkende en ret, l\u00e6se en stregkode. Den er svag, n\u00e5r den g\u00e6tter ud fra tre tal. Forskellen er mellem en AI, der er koblet til l\u00f8bende opdaterede m\u00e5linger, og en chatbot, der svarer en fremmed ud fra hukommelsen.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>Kan jeg genskabe studiet?<\/summary>\n<p>Ja. De 12 prompts, de tidsstemplede r\u00e5 svar, den strukturerede udtr\u00e6kning og scriptsene er offentliggjort som \u00e5bne data (link nederst p\u00e5 siden). Hvert kald er en ny samtale, uden systeminstruktion, med standardindstillingerne.<\/p>\n<\/details>\n<\/section>\n<section aria-labelledby=\"le-suite-title\" class=\"le-section le-suite\" id=\"le-suite\"><header class=\"le-section-heading\"><h2 id=\"le-suite-title\">L\u00e6s ogs\u00e5<\/h2><\/header>\n<ul class=\"le-related\"><li><a href=\"https:\/\/lean-app.com\/da\/calculateur-tdee\/\">TDEE-beregner: den kanoniske formel BMR + NEAT + EAT + TEF <span>Fedtprocentbevidst beregner med opdeling af de 4 metaboliske byggesten.<\/span><\/a><\/li>\n<li><a href=\"https:\/\/lean-app.com\/da\/calculer-vraie-depense-calorique\/\">S\u00e5dan beregner du dit reelle kalorieforbrug: den komplette guide <span>BMR p\u00e5 reel fedtprocent, NEAT per skridt, EAT per pas, TEF per makroer, tilpasning.<\/span><\/a><\/li>\n<li><a href=\"https:\/\/lean-app.com\/da\/calculateur-adaptation-metabolique\/\">Beregner for metabolisk tilpasning: er dit stofskifte bremset? <span>Koefficient 100 til 0 %, tilpasset BMR i kcal\/dag, og hvorn\u00e5r du skal tage en diet break.<\/span><\/a><\/li>\n<li><a href=\"https:\/\/lean-app.com\/da\/10000-pas-calories\/\">10.000 skridt om dagen: hvor mange kalorier det virkelig forbr\u00e6nder <span>Mellem 300 og 550 kcal efter v\u00e6gt. Tabel pr. profil, offentlig formel, beregner.<\/span><\/a><\/li>\n<li><a href=\"https:\/\/lean-app.com\/da\/etude-base-donnees-calories\/\">Studie: 857.655 analyserede produkter, 1 ud af 3 scanninger up\u00e5lidelig <span>Kvaliteten af kaloriedatabaser, m\u00e5lt.<\/span><\/a><\/li>\n<\/ul>\n<\/section>\n<script type=\"application\/ld+json\">{\"@context\": \"https:\/\/schema.org\", \"@type\": \"FAQPage\", \"mainEntity\": [{\"@type\": \"Question\", \"name\": \"ChatGPT peut-il calculer combien de calories je dois manger ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Il donne un chiffre, mais pas une mesure. Sur 291 r\u00e9ponses, aucune IA n'a demand\u00e9 la masse grasse (une seule a demand\u00e9 le nombre de pas), et 97 % des r\u00e9ponses au prompt simple reposent sur une grille d'activit\u00e9 d\u00e9clarative (s\u00e9dentaire, mod\u00e9r\u00e9, actif). Le r\u00e9sultat est une moyenne statistique qui ignore ta composition corporelle et ton activit\u00e9 r\u00e9elle, avec jusqu'\u00e0 1 260 kcal d'\u00e9cart pour la m\u00eame personne.\"}}, {\"@type\": \"Question\", \"name\": \"Pourquoi les IA donnent-elles des chiffres si diff\u00e9rents pour le m\u00eame profil ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Parce qu'elles n'ont pas de mesure. Elles appliquent une formule de population (Mifflin-St Jeor 1990 le plus souvent) puis un multiplicateur d'activit\u00e9 choisi au jug\u00e9. Deux hommes de 78 kg, l'un \u00e0 12 % de masse grasse et 12 000 pas, l'autre \u00e0 28 % et 4 000 pas, re\u00e7oivent la m\u00eame r\u00e9ponse au prompt simple, alors que leur d\u00e9pense r\u00e9elle diff\u00e8re de pr\u00e8s de 1 000 kcal.\"}}, {\"@type\": \"Question\", \"name\": \"Est-ce que donner plus de d\u00e9tails \u00e0 ChatGPT corrige le probl\u00e8me ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"En partie seulement. Avec la masse grasse, les pas et les s\u00e9ances dans le prompt, l'\u00e9cart entre IA reste de 650 kcal sur un m\u00eame profil, la masse grasse n'est r\u00e9ellement utilis\u00e9e dans le calcul que dans 40 % des r\u00e9ponses et les pas dans 42 %. Et surtout, la r\u00e9ponse est fig\u00e9e : elle ne sait pas ce que tu as march\u00e9 ni mang\u00e9 aujourd'hui, ni comment ton m\u00e9tabolisme s'adapte au fil des semaines.\"}}, {\"@type\": \"Question\", \"name\": \"Qu'est-ce que l'adaptation m\u00e9tabolique et pourquoi \u00e7a change la r\u00e9ponse ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"En d\u00e9ficit prolong\u00e9, le m\u00e9tabolisme de base baisse au-del\u00e0 de ce que la perte de poids explique. Un chiffre juste aujourd'hui devient trop haut au bout de quelques semaines. Seules 14 % des r\u00e9ponses d\u00e9taill\u00e9es l'ont mentionn\u00e9, et aucune ne la calcule. C'est la cause la plus fr\u00e9quente des plateaux.\"}}, {\"@type\": \"Question\", \"name\": \"Comment calculer correctement ses calories pour maigrir ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"En reconstruisant la d\u00e9pense brique par brique, TDEE = BMR + NEAT + EAT + TEF, avec le m\u00e9tabolisme de base calcul\u00e9 sur la masse maigre r\u00e9elle, la NEAT sur les pas mesur\u00e9s, l'EAT sur les s\u00e9ances r\u00e9ellement faites, le TEF sur les macros ing\u00e9r\u00e9s, puis en suivant l'\u00e9volution jour apr\u00e8s jour et en corrigeant quand le corps s'adapte. C'est un suivi, pas une r\u00e9ponse en une phrase.\"}}, {\"@type\": \"Question\", \"name\": \"L'IA est-elle inutile pour la nutrition ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Non. L'IA est pr\u00e9cieuse quand elle mesure : estimer une masse grasse sur une photo, reconna\u00eetre un plat, lire un code-barres. Elle est faible quand elle devine \u00e0 partir de trois chiffres. La diff\u00e9rence est entre une IA branch\u00e9e sur des mesures mises \u00e0 jour en continu et un chatbot qui r\u00e9pond de m\u00e9moire \u00e0 un inconnu.\"}}, {\"@type\": \"Question\", \"name\": \"Puis-je reproduire l'\u00e9tude ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Oui. Les 12 prompts, les r\u00e9ponses brutes horodat\u00e9es, l'extraction structur\u00e9e et les scripts sont publi\u00e9s en donn\u00e9es ouvertes (lien en bas de page). Chaque appel est une conversation neuve, sans instruction syst\u00e8me, avec les param\u00e8tres par d\u00e9faut.\"}}]}<\/script><script type=\"application\/ld+json\">{\"@context\": \"https:\/\/schema.org\", \"@type\": \"Dataset\", \"name\": \"Asking consumer AI assistants how many calories to eat to lose weight: 5 models, 6 profiles, 291 answers\", \"description\": \"On a demand\u00e9 291 fois \u00e0 ChatGPT, Gemini et Claude combien manger pour maigrir, pour 6 profils identiques. 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M\u00e9thode, donn\u00e9es brutes et ce qu&rsquo;il faudrait faire \u00e0 la place.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2163","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Perdre du poids avec ChatGPT, \u00e7a marche ? \u00c9tude : 291 r\u00e9ponses, jusqu&#039;\u00e0 1 260 kcal d&#039;\u00e9cart - Lean<\/title>\n<meta name=\"description\" content=\"On a demand\u00e9 291 fois \u00e0 ChatGPT, Gemini et Claude combien manger pour maigrir, pour 6 profils identiques. 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