{"id":"W4410506516","doi":"10.12927/hcpap.2025.27569","title":"Training Data Tell Us a Lot About Whom Health AI Tools Are Likely to Benefit","year":2025,"lang":"en","type":"article","venue":"A Nudge Too Far? A Nudge at All? On Paying People to Be Healthy","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health","funders":"","keywords":"Training (meteorology); Computer science; Data science; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.005460797,0.001309537,0.002530528,0.001162101,0.006252083,0.0003040452,0.003032068,0.001010161,0.0008318176],"category_scores_gemma":[0.004142664,0.001333925,0.0003184982,0.00319353,0.0001333554,0.0007421284,0.002746468,0.003357054,0.005200148],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004960153,"about_ca_system_score_gemma":0.007406789,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02947673,"about_ca_topic_score_gemma":0.1737431,"domain_scores_codex":[0.98383,0.001884291,0.004278332,0.003434539,0.001444163,0.00512864],"domain_scores_gemma":[0.9849142,0.004801444,0.001308367,0.004789616,0.0009508696,0.003235508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001782801,0.0003919191,0.05050889,0.001292069,0.0001059328,0.00004528057,0.0558114,0.0001679557,0.00006703085,0.004123399,0.8140543,0.07164909],"study_design_scores_gemma":[0.0009968288,0.001604564,0.05783078,0.0001348662,0.00005841087,0.00001255681,0.01351757,0.002395737,0.00003985168,0.0003499271,0.9218837,0.001175175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.4059254,0.0008167342,0.001324864,0.5794584,0.002830787,0.005767181,0.001611522,0.0007741959,0.00149095],"genre_scores_gemma":[0.1064042,0.0005175493,0.002428897,0.8829631,0.0002928959,0.001793145,0.0007193576,0.0002911066,0.004589745],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.3035048,"threshold_uncertainty_score":0.9999656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3861112085792702,"score_gpt":0.5145671997662392,"score_spread":0.128455991186969,"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."}}