{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002243686,0.0007741887,0.0007152532,0.0008670552,0.0003086578,0.0007001891,0.001126141,0.0008036282,0.001659103],"category_scores_gemma":[0.01469399,0.0005442973,0.0007059661,0.000499949,0.0008151407,0.001309483,0.001078203,0.001042399,0.0001803173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001279847,"about_ca_system_score_gemma":0.0008220671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01434361,"about_ca_topic_score_gemma":0.01368988,"domain_scores_codex":[0.9994801,0.0003043694,0.00001524748,0.0001287634,0.00003780459,0.00003383188],"domain_scores_gemma":[0.9907712,0.007733238,0.0004763899,0.000477154,0.0003640728,0.0001779821],"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":[0.00002107238,0.00002139779,0.00237371,0.00001565778,0.00002331922,0.00001814977,0.00002612039,0.9921899,0.00009298112,0.0019227,0.0001382194,0.003156714],"study_design_scores_gemma":[0.000003036319,0.000005674062,0.0001636736,0.000001883746,0.000002301198,0.00000188629,0.000003231343,0.9968805,0.00003119366,0.002869585,0.00003561544,0.000001317524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6232766,0.0003385144,0.3721335,0.0007612885,0.0000418573,0.00009411418,0.0007692691,0.0006423231,0.001942571],"genre_scores_gemma":[0.9600416,0.0001272092,0.03842171,0.00008909144,0.0000232381,0.0001009274,0.0005937518,0.00003422898,0.0005682156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01434361,"threshold_uncertainty_score":0.02852029,"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."}}