{"id":"W4409653625","doi":"10.1249/fit.0000000000001058","title":"ChatGPT-Generated Resistance Training Programs","year":2025,"lang":"en","type":"article","venue":"ACSMʼs Health & Fitness Journal","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Resistance (ecology); Training (meteorology); Resistance training; Computer science; Medicine; Biology; Geography; Physical therapy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001362924,0.000902881,0.0003268898,0.0007609008,0.0005199795,0.0009438373,0.001557827,0.0009735443,0.09317852],"category_scores_gemma":[0.01189726,0.0003121438,0.0005531067,0.0003362601,0.0002623203,0.001162237,0.002367474,0.0009889897,0.02775072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003611374,"about_ca_system_score_gemma":0.0006252531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007932603,"about_ca_topic_score_gemma":0.00153455,"domain_scores_codex":[0.9990463,0.0003895,0.00006120152,0.0001657454,0.0002183747,0.0001188247],"domain_scores_gemma":[0.993958,0.002851433,0.0002039757,0.001087383,0.001180243,0.0007189969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002269716,0.001836461,0.007582993,0.001690996,0.00008510151,0.001434092,0.0031888,0.004993038,0.01137278,0.004102497,0.3906773,0.5707662],"study_design_scores_gemma":[0.001379899,0.00336472,0.02895603,0.001638897,0.0002401605,0.002029883,0.002124532,0.04317483,0.03149924,0.01357218,0.8716607,0.0003590363],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1667654,0.0008573955,0.3316415,0.00489324,0.003655645,0.006400167,0.02036655,0.2190056,0.2464144],"genre_scores_gemma":[0.4954946,0.0008466296,0.2697965,0.003591422,0.0007496857,0.009155681,0.02232327,0.01354718,0.184495],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09317852,"threshold_uncertainty_score":0.3117132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2410407296387163,"score_gpt":0.4724716455118277,"score_spread":0.2314309158731114,"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."}}