{"id":"W4229454935","doi":"10.2196/35696","title":"A Model for Estimating Biological Age From Physiological Biomarkers of Healthy Aging: Cross-sectional Study","year":2022,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Adipokines, Inflammation, and Metabolic Diseases","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cross-sectional study; Healthy aging; Medicine; Biological age; Gerontology; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003978095,0.0001473713,0.0003569835,0.0001040459,0.0003400825,0.00001861409,0.0001275073,0.00004034406,0.0001553389],"category_scores_gemma":[0.0001669562,0.0001205518,0.0001695585,0.0001651668,0.00009226631,0.00006255985,0.0001216869,0.0001468274,0.000001440345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006603446,"about_ca_system_score_gemma":0.0001145535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008352062,"about_ca_topic_score_gemma":0.000002216108,"domain_scores_codex":[0.9985165,0.00008691494,0.000476413,0.0003764113,0.0002938766,0.0002498596],"domain_scores_gemma":[0.999235,0.000168936,0.0001974838,0.0002020239,0.00008163269,0.0001148747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001579339,0.002258163,0.9423313,0.0002106508,0.0003634479,0.00004067573,0.003511258,0.0285457,0.01675875,0.0002349898,0.0008170419,0.003348739],"study_design_scores_gemma":[0.002457766,0.0004072809,0.7183385,0.00001658645,0.00005208633,0.000007217855,0.0006394162,0.2769898,0.00003296194,0.00072734,0.0001995465,0.0001314659],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907638,0.0001546317,0.007334797,0.00007712533,0.0002151555,0.001124746,0.0001428468,0.0001087311,0.00007815002],"genre_scores_gemma":[0.9876744,0.000002483014,0.01058609,0.0003223719,0.0003589722,0.000630624,0.0003186729,0.00001602241,0.00009040199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2484441,"threshold_uncertainty_score":0.4915959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0952832948162266,"score_gpt":0.3849979630396765,"score_spread":0.2897146682234499,"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."}}