{"id":"W4408277156","doi":"10.2196/64473","title":"Artificial Intelligence-Driven Biological Age Prediction Model Using Comprehensive Health Checkup Data: Development and Validation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Health Promotion and Cardiovascular Prevention","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; 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":[0.006632251,0.000969333,0.0009439348,0.0008605984,0.0003389783,0.0005725905,0.001176127,0.0007578827,0.001097633],"category_scores_gemma":[0.006635309,0.0003441332,0.001052987,0.0006079684,0.0003544541,0.0005829581,0.0007157087,0.0009589526,0.0003018976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001014692,"about_ca_system_score_gemma":0.001801773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01855157,"about_ca_topic_score_gemma":0.00921653,"domain_scores_codex":[0.9992303,0.0004058457,0.00005261737,0.0001522238,0.0000964038,0.00006269024],"domain_scores_gemma":[0.9942959,0.00355552,0.0003090773,0.000341395,0.001340416,0.0001576296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006024548,0.001521742,0.1473725,0.0001764872,0.0006314226,0.0002878003,0.0001564502,0.7685682,0.001416766,0.0008891884,0.002120327,0.07625666],"study_design_scores_gemma":[0.00002268226,0.0001772208,0.009227001,0.00001097368,0.00003942335,0.00002175103,0.00001717212,0.9898723,0.0002961216,0.0001514216,0.0001550617,0.000008834741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9590321,0.0002896523,0.03855275,0.0001449239,0.00003387698,0.0002342298,0.0007018435,0.0002473351,0.0007633417],"genre_scores_gemma":[0.9741708,0.0001341492,0.02356192,0.00004247208,0.00001397878,0.0002087523,0.00140462,0.00001083685,0.0004525497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01855157,"threshold_uncertainty_score":0.03688717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2676205564612297,"score_gpt":0.445163564099685,"score_spread":0.1775430076384553,"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."}}