{"id":"W4413187108","doi":"10.2196/71807","title":"Changes in Skeletal Muscle Mass Index With Personalized Exercise and Meal Photo Analysis via Nutrition Applications: Single-Arm Pilot Study","year":2025,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Meal; Medicine; Skeletal muscle; Body mass index; Physical medicine and rehabilitation; Internal medicine; Computer science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003935365,0.001692862,0.001716592,0.0006018629,0.00129503,0.0005673011,0.0008606825,0.001313992,0.004150252],"category_scores_gemma":[0.002582328,0.0008153116,0.001311795,0.0003969829,0.00111787,0.001044872,0.0008840683,0.002145661,0.001005667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007271413,"about_ca_system_score_gemma":0.0014828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002577754,"about_ca_topic_score_gemma":0.003838148,"domain_scores_codex":[0.9985475,0.0006503881,0.00008838122,0.0002269611,0.0002318838,0.0002549199],"domain_scores_gemma":[0.99831,0.0003403045,0.000301374,0.0002149772,0.0003234616,0.000509994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"nonrandomized_trial","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.4015887,0.5031143,0.02245135,0.0006129753,0.0007959182,0.0001386163,0.0007558652,0.0006814735,0.02454907,0.00004387973,0.0009072061,0.04436055],"study_design_scores_gemma":[0.02331174,0.92853,0.04416193,0.00002061047,0.0002773908,0.00003352506,0.0001738352,0.0004357624,0.002664302,0.00003748095,0.0003277691,0.00002559345],"study_design_candidate":"nonrandomized_trial","study_design_consensus":"nonrandomized_trial","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995873,0.00007551459,0.0005167311,0.00004509788,0.00003713265,0.002853335,0.0002195449,0.00003754152,0.0003419804],"genre_scores_gemma":[0.9813642,0.0001757063,0.003455261,0.0002474352,0.0001365426,0.01197571,0.0004731528,0.00001776437,0.002154254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004150252,"threshold_uncertainty_score":0.02081245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08232190977945873,"score_gpt":0.4296326546596408,"score_spread":0.347310744880182,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}