{"id":"W3117155717","doi":"10.1093/geroni/igaa057.1576","title":"Building, testing, and learning from network models of human aging","year":2020,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Gompertz function; Frailty Index; Observational study; Exponential function; Econometrics; Computer science; Machine learning; Statistics; Mathematics; Gerontology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008393081,0.0001255548,0.0001677073,0.00007433222,0.0001841059,0.00002644808,0.0001180358,0.00004614949,0.0001453319],"category_scores_gemma":[0.0003721192,0.0001499182,0.00001078472,0.001149244,0.0001017295,0.0003576041,0.000237987,0.000424409,0.00001133367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009488725,"about_ca_system_score_gemma":0.000008168564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001269294,"about_ca_topic_score_gemma":0.00002222048,"domain_scores_codex":[0.9984232,0.0001180311,0.0005063794,0.0004362583,0.0002367994,0.000279381],"domain_scores_gemma":[0.9993263,0.0002147102,0.0002841222,0.0001096102,0.00001280773,0.00005243221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002135997,0.00001049039,0.7328885,0.00001676922,0.000004142048,0.000004773665,0.002479012,0.1790481,0.06181986,0.0006972459,0.00004028786,0.02298868],"study_design_scores_gemma":[0.0008571817,0.00008017207,0.6098684,0.0003811111,0.0000125673,0.000002001979,0.0006617802,0.3574468,0.005327457,0.02397615,0.0009316568,0.0004547193],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9639431,0.0000352063,0.03155387,0.0005203624,0.00002533281,0.0001530285,9.676614e-7,0.00005101593,0.003717152],"genre_scores_gemma":[0.9769023,0.000005522581,0.02171933,0.0012357,0.00008772058,0.000008488784,0.000006226529,0.00002115508,0.00001352479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1783987,"threshold_uncertainty_score":0.6113487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05708330139004134,"score_gpt":0.2891616030731162,"score_spread":0.2320783016830749,"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."}}