{"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\/es\/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\/es\/\" aria-label=\"Inicio Lean\"><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\/es\/tdee-calculator\/\">Calculadora TDEE<\/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=\"Descargar en el 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=\"Disponible en 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; 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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\">Estudio \u00b7 Perder peso con la IA<\/p>\n<h1 id=\"le-title\"><span class=\"le-title-line\">Perder peso<\/span> <span class=\"le-title-line\">con ChatGPT,<\/span> <span class=\"le-title-accent\">\u00bffunciona?<\/span> <span class=\"le-title-follow\">Le hicimos la pregunta 291 veces a 5 IA<\/span><\/h1><p class=\"le-deck\">La misma persona, la misma pregunta, hasta 1 260 kcal de diferencia. Esto es lo que responden las IA, y lo que no pueden hacer.<\/p>\n<div class=\"le-hero-actions\" data-visual-copy=\"\"><a class=\"le-explore\" href=\"#le-resume\">Explorar el estudio<\/a><span class=\"le-scroll-cue\">\u2193<\/span><\/div><p class=\"le-byline\">Estudio independiente de El equipo Lean, la app que recalcula tu gasto cada d\u00eda a partir de tus medidas \u00b7 9 de septiembre de 2026 \u00b7 Datos abiertos<\/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 Prompt simple<\/span><div class=\"le-answer le-answer-0\" style=\"--order:0\"><span class=\"le-answer-name\">ChatGPT (GPT-5.5)<\/span><strong>1 600 a 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 a 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 a 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 a 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 a 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>de diferencia para el mismo perfil, prompt simple<\/span><\/li>\n<li class=\"le-hero-stat le-mini-stat\"><strong>0 %<\/strong><span>piden la grasa corporal<\/span><\/li>\n<li class=\"le-hero-stat le-mini-stat\"><strong>97 %<\/strong><span>responden con una tabla \u00ab sedentario \/ activo \u00bb<\/span><\/li>\n<li class=\"le-hero-stat le-mini-stat\"><strong>14 %<\/strong><span>hablan de adaptaci\u00f3n metab\u00f3lica<\/span><\/li>\n<\/ul>\n<\/section>\n<nav aria-label=\"En este estudio\" class=\"le-nav\"><a href=\"#le-resume\">Resumen<\/a><a href=\"#le-simple\">Resultados<\/a><a href=\"#le-suivi\">El verdadero tema<\/a><a href=\"#le-donnees\">Datos<\/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\">Resumen<\/span><h2 id=\"le-resume-title\">El estudio en 30 segundos<\/h2><\/header>\n<ul class=\"le-summary-list\"><li><span class=\"le-summary-num\">1<\/span><span class=\"le-summary-text\"><strong>291 respuestas<\/strong> de ChatGPT, Gemini y Claude a la pregunta \u00ab cu\u00e1ntas calor\u00edas para adelgazar ? \u00bb, para 6 perfiles id\u00e9nticos.<\/span><\/li>\n<li><span class=\"le-summary-num\">2<\/span><span class=\"le-summary-text\">Prompt simple (edad, peso, altura): a la misma persona se le dice <strong>de 1 500 a 2 700 kcal<\/strong> seg\u00fan la IA y el momento.<\/span><\/li>\n<li><span class=\"le-summary-num\">3<\/span><span class=\"le-summary-text\"><strong>0 %<\/strong> de respuestas piden la grasa corporal. <strong>97 %<\/strong> devuelven una cuadr\u00edcula \u00absedentario \/ moderado \/ activo\u00bb, la f\u00f3rmula de 1990.<\/span><\/li>\n<li><span class=\"le-summary-num\">4<\/span><span class=\"le-summary-text\">Prompt completo (grasa corporal, pasos, sesiones): a\u00fan <strong>650 kcal<\/strong> de diferencia, y la grasa corporal solo se utiliza en <strong>40 %<\/strong> los c\u00e1lculos.<\/span><\/li>\n<li><span class=\"le-summary-num\">5<\/span><span class=\"le-summary-text\">Ninguna IA hace seguimiento al d\u00eda siguiente: pasos del d\u00eda, comidas, efecto t\u00e9rmico, adaptaci\u00f3n metab\u00f3lica (<strong>14 %<\/strong> la mencionan). La cifra queda fijada el d\u00eda 1.<\/span><\/li>\n<\/ul>\n<div class=\"le-summary-verdict\"><strong>Veredicto.<\/strong> Puede funcionar por suerte, no por m\u00e9todo: sin medici\u00f3n ni actualizaci\u00f3n diaria, la respuesta es una media de poblaci\u00f3n fijada el primer d\u00eda.<\/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 M\u00e9todo<\/span><h2 id=\"le-methode-title\">Lo que hicimos<\/h2><\/header>\n<ul class=\"le-method-stats\"><li><strong>6<\/strong><span>perfiles id\u00e9nticos, de la deportista al hombre sedentario<\/span><\/li>\n<li><strong>2<\/strong><span>niveles de prompt: simple, luego completo<\/span><\/li>\n<li><strong>5<\/strong><span>IA de consumo general, conversaci\u00f3n nueva cada vez<\/span><\/li>\n<li><strong>291<\/strong><span>respuestas con marca de tiempo, publicadas en datos abiertos<\/span><\/li>\n<\/ul>\n<p class=\"le-method-note\">ChatGPT (GPT-5.5 y GPT-5.4 mini), Gemini (3.7 Flash y 3.1 Pro), Claude Opus. Franc\u00e9s e ingl\u00e9s, 2 a 3 repeticiones, sin ninguna instrucci\u00f3n. La l\u00ednea negra de los gr\u00e1ficos: el objetivo calculado componente a componente sobre los datos medidos (BMR sobre masa magra, pasos, sesiones, TEF, d\u00e9ficit de 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 Resultado 1<\/span><h2 id=\"le-simple-title\">Prompt simple: de 1 500 a 2 700 kcal para la misma persona<\/h2><\/header>\n<p class=\"le-result-intro\">\u00abSoy un hombre de 32 a\u00f1os, 78 kg, 180 cm, quiero perder peso, \u00bfcu\u00e1ntas calor\u00edas al d\u00eda?\u00bb La pregunta tal como la hacen millones de personas.<\/p>\n<div class=\"le-chart-controls\" data-controls=\"simple\" hidden=\"\"><div aria-label=\"Perfiles, prompt simple\" 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\">Mostrar todo<\/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\">Hombre 32 a\u00f1os, 78 kg, 180 cm, 12 % MG, 12 000 pasos, 4 sesiones de musculaci\u00f3n\/sem<\/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 a 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 a 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 a 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 a 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 a 2 600<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 500 a 2 700 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">1 200 kcal de diferencia<\/strong> (28 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (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\">Hombre 32 a\u00f1os, 78 kg, 180 cm, 28 % MG, 4 000 pasos, ning\u00fan deporte<\/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 a 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 a 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 a 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 a 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 a 2 500<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 500 a 2 760 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">1 260 kcal de diferencia<\/strong> (28 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (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\">Mujer 28 a\u00f1os, 62 kg, 165 cm, 22 % MG, 9 000 pasos, 3 sesiones de fitness\/sem<\/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 a 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 a 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 a 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 a 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 a 1 900<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 130 a 2 000 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">870 kcal de diferencia<\/strong> (25 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (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\">Mujer 45 a\u00f1os, 70 kg, 165 cm, 35 % MG, 3 500 pasos, ning\u00fan deporte<\/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 a 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 a 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 a 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 a 1 800<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 100 a 2 000 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">900 kcal de diferencia<\/strong> (22 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (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\">Hombre 50 a\u00f1os, 95 kg, 178 cm, 30 % MG, 6 000 pasos, 2 caminatas\/sem<\/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 a 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 a 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 a 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 a 2 300<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 500 a 2 550 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">1 050 kcal de diferencia<\/strong> (22 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (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\">Mujer 24 a\u00f1os, 55 kg, 170 cm, 18 % MG, 14 000 pasos, 5 carreras\/sem<\/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 a 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 a 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 a 2 200<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 200 a 2 200 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">1 000 kcal de diferencia<\/strong> (16 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (1 735 kcal).<\/figcaption>\n<\/figure>\n<\/div><div class=\"le-behavior\"><h3 class=\"le-behavior-title\">Comportamiento de las IA, prompt simple (147 respuestas)<\/h3><ul class=\"le-behavior-list\"><li data-percent=\"0\" style=\"--percent:0%\"><strong>0 %<\/strong><span>piden el porcentaje de grasa corporal<\/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>piden el n\u00famero de pasos diarios<\/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>utilizan una cuadr\u00edcula de actividad declarativa<\/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>citan Mifflin-St Jeor o 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>mencionan el efecto t\u00e9rmico de los alimentos<\/span><span aria-hidden=\"true\" class=\"le-behavior-meter\"><i><\/i><\/span><\/li>\n<\/ul>\n<\/div><div class=\"le-insight\">P1 y P2 plantearon <strong>exactamente la misma pregunta<\/strong> (misma edad, peso, talla) y recibieron la misma cuadr\u00edcula. Sin embargo, su gasto real difiere en casi 1 000 kcal al d\u00eda: 12 % de grasa corporal y 12 000 pasos por un lado, 28 % y 4 000 pasos por el otro.<\/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 Resultado 2<\/span><h2 id=\"le-complet-title\">Prompt completo: a\u00fan 650 kcal de diferencia<\/h2><\/header>\n<p class=\"le-result-intro\">Damos todo: grasa corporal, pasos por d\u00eda, sesiones, y \u00abdame una cifra precisa\u00bb. Todas obedecen. Una cifra precisa no es una cifra correcta.<\/p>\n<div class=\"le-chart-controls\" data-controls=\"complet\" hidden=\"\"><div aria-label=\"Perfiles, prompt completo\" 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\">Mostrar todo<\/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\">Hombre 32 a\u00f1os, 78 kg, 180 cm, 12 % MG, 12 000 pasos, 4 sesiones de musculaci\u00f3n\/sem<\/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 a 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 a 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 a 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 a 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 a 2 450<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">2 100 a 2 750 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">650 kcal de diferencia<\/strong> (28 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (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\">Hombre 32 a\u00f1os, 78 kg, 180 cm, 28 % MG, 4 000 pasos, ning\u00fan deporte<\/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 a 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 a 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 a 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 a 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 a 1 950<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 400 a 2 000 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">600 kcal de diferencia<\/strong> (28 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (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\">Mujer 28 a\u00f1os, 62 kg, 165 cm, 22 % MG, 9 000 pasos, 3 sesiones de fitness\/sem<\/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 a 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 a 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 a 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 a 1 900<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 450 a 1 900 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">450 kcal de diferencia<\/strong> (22 respuestas). L\u00ednea negra: objetivo calculado componente a componente sobre los datos medidos (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\">Mujer 45 a\u00f1os, 70 kg, 165 cm, 35 % MG, 3 500 pasos, ning\u00fan deporte<\/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 a 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 a 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 a 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 a 1 600<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 200 a 1 600 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">400 kcal de diferencia<\/strong> (22 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (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\">Hombre 50 a\u00f1os, 95 kg, 178 cm, 30 % MG, 6 000 pasos, 2 caminatas\/sem<\/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 a 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 a 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 a 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 a 2 100<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 600 a 2 200 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">600 kcal de diferencia<\/strong> (22 respuestas). L\u00ednea negra: objetivo obtenido componente a componente sobre los datos medidos (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\">Mujer 24 a\u00f1os, 55 kg, 170 cm, 18 % MG, 14 000 pasos, 5 carreras\/sem<\/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 a 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 a 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 a 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 a 2 400<\/span><\/div><\/div><figcaption class=\"le-chart-caption\">Todas las IA combinadas: <strong class=\"le-caption-range\">1 850 a 2 500 kcal<\/strong>, es decir <strong class=\"le-caption-gap\">650 kcal de diferencia<\/strong> (19 respuestas). L\u00ednea negra: objetivo calculado componente a componente sobre los datos medidos (1 735 kcal).<\/figcaption>\n<\/figure>\n<\/div><div class=\"le-behavior\"><h3 class=\"le-behavior-title\">Comportamiento de las IA, prompt completo (144 respuestas)<\/h3><ul class=\"le-behavior-list\"><li data-percent=\"40\" style=\"--percent:40%\"><strong>40 %<\/strong><span>utilizan realmente la grasa corporal proporcionada<\/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>convierten los pasos proporcionados en calor\u00edas<\/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>mencionan la adaptaci\u00f3n metab\u00f3lica<\/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>mencionan el efecto t\u00e9rmico de los alimentos<\/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>dan una cifra \u00fanica, como se pidi\u00f3<\/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\">La prueba P1 frente a P2: mismo peso, cuerpos diferentes<\/h3><ul class=\"le-comparison-stats\"><li><strong>699 <small>kcal<\/small><\/strong><span>de diferencia entre P1 y P2 seg\u00fan las IA (media)<\/span><\/li>\n<li><strong>970 <small>kcal<\/small><\/strong><span>de diferencia cuando se calcula componente a componente<\/span><\/li>\n<li><strong>+324 <small>kcal<\/small><\/strong><span>de m\u00e1s para el perfil sedentario con 28 % de grasa corporal<\/span><\/li>\n<\/ul>\n<\/div><div class=\"le-insight\">Las IA ven la diferencia entre los dos hombres, pero la subestiman: ajustan una f\u00f3rmula de poblaci\u00f3n en lugar de medir. El perfil sedentario, el que \u00abhace todo bien\u00bb, recibe un objetivo demasiado alto y no pierde nada.<\/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 El verdadero tema<\/span><h2 id=\"le-suivi-title\">El problema no es el d\u00eda 1, son los <span class=\"le-time-headline\">89 d\u00edas siguientes<\/span><\/h2><\/header>\n<p class=\"le-time-intro\">El 78 % de las respuestas detalladas aconsejan \u00abpesarte y ajustar\u00bb. Ninguna lo hace por ti.<\/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=\"\">D\u00eda<\/span><span class=\"le-dial-day\" data-current-day=\"\">1<\/span><\/div><span class=\"le-dial-caption\">La cifra est\u00e1 fijada en el d\u00eda 1.<\/span><\/div><ul class=\"le-timeline\"><li><strong><span>D\u00eda<\/span> <b>1<\/b><\/strong><span>El chatbot recibe un peso y responde una vez.<\/span><\/li>\n<li><strong><span>D\u00eda<\/span> <b>2<\/b><\/strong><span>Has caminado 4 000 pasos en lugar de 11 000. No lo sabe.<\/span><\/li>\n<li><strong><span>Semana<\/span> <b>3<\/b><\/strong><span>Has hecho 6 sesiones y cambiado tus macros. No lo sabe.<\/span><\/li>\n<li><strong><span>D\u00eda<\/span> <b>90<\/b><\/strong><span>Has perdido 4 kg, tu metabolismo ha bajado y luego se ha adaptado. Sigue sin saberlo.<\/span><\/li>\n<\/ul>\n<\/div><div class=\"le-checklists\"><div class=\"le-checklist le-checklist-no\"><h3>Lo que el chatbot no sabe<\/h3><ul><li><span>\u2715<\/span><span>Tus pasos del d\u00eda<\/span><\/li>\n<li><span>\u2715<\/span><span>Tus comidas del d\u00eda y su efecto t\u00e9rmico<\/span><\/li>\n<li><span>\u2715<\/span><span>Tu grasa corporal real, y su evoluci\u00f3n<\/span><\/li>\n<li><span>\u2715<\/span><span>La adaptaci\u00f3n de tu metabolismo a lo largo de las semanas<\/span><\/li>\n<li><span>\u2715<\/span><span>Ninguna curva, ning\u00fan gr\u00e1fico de tu gasto<\/span><\/li>\n<\/ul>\n<\/div><div class=\"le-checklist le-checklist-yes\"><h3>Lo que un seguimiento real exige<\/h3><ul><li><span>\u2713<\/span><span>Gasto recalculado cada d\u00eda a partir de medidas<\/span><\/li>\n<li><span>\u2713<\/span><span>Objetivo que se mueve con los pasos y las sesiones<\/span><\/li>\n<li><span>\u2713<\/span><span>Grasa corporal re-medida regularmente<\/span><\/li>\n<li><span>\u2713<\/span><span>Correcci\u00f3n autom\u00e1tica de la adaptaci\u00f3n metab\u00f3lica<\/span><\/li>\n<li><span>\u2713<\/span><span>Una curva legible de tu TDEE y de su evoluci\u00f3n<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><div class=\"le-verdict\"><strong>Veredicto: \u00bfperder peso con ChatGPT funciona?<\/strong> Por suerte, a veces. Por m\u00e9todo, no: sin medida ni actualizaci\u00f3n diaria, la respuesta sigue siendo una estimaci\u00f3n de poblaci\u00f3n fijada el primer d\u00eda. La prueba se puede repetir en cinco minutos con tu propio perfil.<\/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 \u00bfY Lean?<\/span><h2 id=\"le-app-title\">La IA que mide frente a la IA que adivina<\/h2><\/header>\n<p class=\"le-app-intro\">Lean tambi\u00e9n utiliza la IA, pero para medir: BodyScan para la grasa corporal, escaneo de foto para el plato, pod\u00f3metro para los pasos. Luego recalcula cada d\u00eda los cinco componentes de tu gasto y traza la curva.<\/p>\n<div class=\"le-app-panel\"><div class=\"le-feature-list\"><span class=\"le-feature le-feature-0\">BMR sobre masa magra medida<\/span><span class=\"le-feature le-feature-1\">NEAT sobre pasos reales<\/span><span class=\"le-feature le-feature-2\">EAT por sesi\u00f3n<\/span><span class=\"le-feature le-feature-3\">TEF seg\u00fan los macros<\/span><span class=\"le-feature le-feature-4\">Adaptaci\u00f3n metab\u00f3lica<\/span><\/div><strong>Lean mide, recalcula y sigue, cada d\u00eda<\/strong><span>Primera app para calcular la adaptaci\u00f3n metab\u00f3lica. Descarga gratuita, prueba de 7 d\u00edas en la suscripci\u00f3n anual. 4,7\/5 en el App Store, m\u00e1s de 10 000 usuarios.<\/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\">Datos<\/span><h2 id=\"le-donnees-title\">Los datos, perfil por perfil<\/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 Hombre 32 a\u00f1os, 78 kg, 180 cm, 12 % grasa corporal, 12 000 pasos, 4 muscu\/sem<\/h3><div class=\"le-data-values\">Prompt simple: <strong>1 500 a 2 700 kcal<\/strong> (28 respuestas) \u00b7 Prompt completo: <strong>2 100 a 2 750 kcal<\/strong> (28 respuestas) \u00b7 Objetivo componente a componente: <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 Hombre 32 a\u00f1os, 78 kg, 180 cm, 28 % grasa corporal, 4 000 pasos, ning\u00fan deporte<\/h3><div class=\"le-data-values\">Prompt simple: <strong>1 500 a 2 760 kcal<\/strong> (28 respuestas) \u00b7 Prompt completo: <strong>1 400 a 2 000 kcal<\/strong> (28 respuestas) \u00b7 Objetivo componente a componente: <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 Mujer 28 a\u00f1os, 62 kg, 165 cm, 22 % grasa corporal, 9 000 pasos, 3 fitness\/sem<\/h3><div class=\"le-data-values\">Prompt simple: <strong>1 130 a 2 000 kcal<\/strong> (25 respuestas) \u00b7 Prompt completo: <strong>1 450 a 1 900 kcal<\/strong> (22 respuestas) \u00b7 Objetivo componente a componente: <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 Mujer 45 a\u00f1os, 70 kg, 165 cm, 35 % grasa corporal, 3 500 pasos, ning\u00fan deporte<\/h3><div class=\"le-data-values\">Prompt simple: <strong>1 100 a 2 000 kcal<\/strong> (22 respuestas) \u00b7 Prompt completo: <strong>1 200 a 1 600 kcal<\/strong> (22 respuestas) \u00b7 Objetivo componente a componente: <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 Hombre 50 a\u00f1os, 95 kg, 178 cm, 30 % grasa corporal, 6 000 pasos, 2 marchas\/sem<\/h3><div class=\"le-data-values\">Prompt simple: <strong>1 500 a 2 550 kcal<\/strong> (22 respuestas) \u00b7 Prompt completo: <strong>1 600 a 2 200 kcal<\/strong> (22 respuestas) \u00b7 Objetivo componente a componente: <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 Mujer 24 a\u00f1os, 55 kg, 170 cm, 18 % MG, 14 000 pasos, 5 carreras\/sem<\/h3><div class=\"le-data-values\">Prompt simple: <strong>1 200 a 2 200 kcal<\/strong> (16 respuestas) \u00b7 Prompt completo: <strong>1 850 a 2 500 kcal<\/strong> (19 respuestas) \u00b7 Objetivo componente a componente: <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\">Variabilidad de una misma IA en el mismo prompt repetido (prompt completo, diferencia media entre repeticiones): 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\">Conjunto de datos completo (prompts, 291 respuestas brutas, extracci\u00f3n, scripts): <a href=\"https:\/\/doi.org\/10.5281\/zenodo.22662006\" rel=\"noopener\">Zenodo, DOI 10.5281\/zenodo.22662006<\/a>, licencia CC BY 4.0.<\/p>\n<details class=\"le-disclosure\"><summary>M\u00e9todo detallado y l\u00edmites<\/summary>\n<p>Modelos consultados por API con los par\u00e1metros por defecto y sin instrucci\u00f3n del sistema: GPT-5.5 y GPT-5.4 mini (OpenAI), Gemini 3.7 Flash y Gemini 3.1 Pro (Google). Claude Opus (Anthropic) consultado mediante la interfaz de l\u00ednea de comandos oficial con un prompt del sistema neutro y sin ning\u00fan contexto. Seis perfiles, dos niveles de prompt, franc\u00e9s e ingl\u00e9s, 2 a 3 repeticiones por combinaci\u00f3n, 291 respuestas recopiladas el 8 de septiembre de 2026 (Gemini 3.1 Pro: 27 respuestas, l\u00edmite de velocidad de la API; otros modelos: 48 a 72).<\/p>\n<p>Lectura de las respuestas: un extractor autom\u00e1tico (GPT-5.4 mini, temperatura 0, esquema JSON estricto) identifica el objetivo de ingesta recomendado (m\u00edn y m\u00e1x cuando se da un rango o una tabla) y los comportamientos (pregunta hecha antes de responder, tabla de actividad, uso real de la grasa corporal y de los pasos proporcionados, menci\u00f3n de la adaptaci\u00f3n metab\u00f3lica y del efecto t\u00e9rmico). La extracci\u00f3n se publica con las respuestas brutas, l\u00ednea por l\u00ednea.<\/p>\n<p>L\u00edmites: perfiles ficticios; f\u00f3rmulas de referencia p\u00fablicas (Katch-McArdle sobre la masa magra, compendio de Ainsworth 2011, TEF al 10 %) que sirven de referencia, no de verdad de campo; los modelos evolucionan y las respuestas cambian de una semana a otra, lo cual forma parte del hallazgo. Lean edita este estudio y vende una aplicaci\u00f3n de seguimiento: el m\u00e9todo y los datos son abiertos para que cualquiera pueda reproducirlo.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>Fuentes cient\u00edficas<\/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>Science<\/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\">Estudio publicado por El equipo Lean. Contacto de prensa: franckbarriere@lean-app.com. No es un consejo m\u00e9dico.<\/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\">Preguntas frecuentes<\/h2><\/header>\n<details class=\"le-disclosure\"><summary>\u00bfPuede ChatGPT calcular cu\u00e1ntas calor\u00edas debo comer?<\/summary>\n<p>Da una cifra, pero no una medida. Sobre 291 respuestas, ninguna IA pidi\u00f3 la grasa corporal (solo una pidi\u00f3 el n\u00famero de pasos), y el 97 % de las respuestas al prompt simple se basan en una tabla de actividad declarativa (sedentario, moderado, activo). El resultado es una media estad\u00edstica que ignora tu composici\u00f3n corporal y tu actividad real, con hasta 1 260 kcal de diferencia para la misma persona.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>\u00bfPor qu\u00e9 las IA dan cifras tan distintas para el mismo perfil?<\/summary>\n<p>Porque no tienen una medida. Aplican una f\u00f3rmula de poblaci\u00f3n (Mifflin-St Jeor 1990, la mayor\u00eda de las veces) y luego un multiplicador de actividad elegido a ojo. Dos hombres de 78 kg, uno con 12 % de grasa corporal y 12 000 pasos, el otro con 28 % y 4 000 pasos, reciben la misma respuesta al prompt simple, aunque su gasto real difiera en casi 1 000 kcal.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>\u00bfDar m\u00e1s detalles a ChatGPT corrige el problema?<\/summary>\n<p>Solo en parte. Con la grasa corporal, los pasos y las sesiones en el prompt, la diferencia entre IA sigue siendo de 650 kcal sobre un mismo perfil, la grasa corporal solo se usa realmente en el c\u00e1lculo en el 40 % de las respuestas y los pasos en el 42 %. Y sobre todo, la respuesta est\u00e1 fija: no sabe cu\u00e1nto has caminado ni comido hoy, ni c\u00f3mo se adapta tu metabolismo a lo largo de las semanas.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>\u00bfQu\u00e9 es la adaptaci\u00f3n metab\u00f3lica y por qu\u00e9 cambia la respuesta?<\/summary>\n<p>En un d\u00e9ficit prolongado, el metabolismo basal baja m\u00e1s all\u00e1 de lo que explica la p\u00e9rdida de peso. Un n\u00famero que hoy es correcto se vuelve demasiado alto al cabo de unas semanas. Solo el 14 % de las respuestas detalladas lo mencion\u00f3, y ninguna lo calcula. Es la causa m\u00e1s frecuente de los estancamientos.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>\u00bfC\u00f3mo calcular correctamente tus calor\u00edas para adelgazar?<\/summary>\n<p>Reconstruyendo el gasto componente a componente, TDEE = BMR + NEAT + EAT + TEF, con el metabolismo basal calculado sobre la masa magra real, la NEAT sobre los pasos medidos, la EAT sobre las sesiones realmente hechas, el TEF sobre los macros ingeridos, y luego siguiendo la evoluci\u00f3n d\u00eda tras d\u00eda y corrigiendo cuando el cuerpo se adapta. Es un seguimiento, no una respuesta en una frase.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>\u00bfLa IA es in\u00fatil para la nutrici\u00f3n?<\/summary>\n<p>No. La IA es valiosa cuando mide: estimar la grasa corporal en una foto, reconocer un plato, leer un c\u00f3digo de barras. Es d\u00e9bil cuando adivina a partir de tres n\u00fameros. La diferencia est\u00e1 entre una IA conectada a medidas actualizadas continuamente y un chatbot que responde de memoria a un desconocido.<\/p>\n<\/details>\n<details class=\"le-disclosure\"><summary>\u00bfPuedo reproducir el estudio?<\/summary>\n<p>S\u00ed. Los 12 prompts, las respuestas brutas con marca de tiempo, la extracci\u00f3n estructurada y los scripts est\u00e1n publicados en datos abiertos (enlace al final de la p\u00e1gina). Cada llamada es una conversaci\u00f3n nueva, sin instrucci\u00f3n del sistema, con los par\u00e1metros por defecto.<\/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\">Lecturas relacionadas<\/h2><\/header>\n<ul class=\"le-related\"><li><a href=\"https:\/\/lean-app.com\/es\/calculateur-tdee\/\">Calculadora TDEE: la f\u00f3rmula can\u00f3nica BMR + NEAT + EAT + TEF <span>Calculadora bodyfat-aware con desglose de los 4 bloques metab\u00f3licos.<\/span><\/a><\/li>\n<li><a href=\"https:\/\/lean-app.com\/es\/calculer-vraie-depense-calorique\/\">C\u00f3mo calcular tu gasto cal\u00f3rico real: la gu\u00eda completa <span>BMR sobre grasa corporal real, NEAT por pasos, EAT por sesi\u00f3n, TEF por macros, adaptaci\u00f3n.<\/span><\/a><\/li>\n<li><a href=\"https:\/\/lean-app.com\/es\/calculateur-adaptation-metabolique\/\">Calculadora de adaptaci\u00f3n metab\u00f3lica: \u00bftu metabolismo se ha frenado? <span>Coeficiente 100 a 0 %, BMR adaptado en kcal\/d\u00eda, y cu\u00e1ndo hacer un diet break.<\/span><\/a><\/li>\n<li><a href=\"https:\/\/lean-app.com\/es\/10000-pas-calories\/\">10 000 pasos al d\u00eda: cu\u00e1ntas calor\u00edas quema realmente <span>Entre 300 y 550 kcal seg\u00fan tu peso. Tabla por perfil, f\u00f3rmula p\u00fablica, calculadora.<\/span><\/a><\/li>\n<li><a href=\"https:\/\/lean-app.com\/es\/etude-base-donnees-calories\/\">Estudio: 857 655 productos analizados, 1 escaneo de cada 3 no fiable <span>La calidad de las bases de datos de calor\u00edas, medida.<\/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. 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