{"id":"W3111441242","doi":"10.1093/geroni/igaa057.3387","title":"Forecasting Individual Aging Trajectories and Survival with an Interpretable Network Model","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":"Baseline (sea); Computer science; Scalability; Machine learning; State variable; Artificial intelligence; Longitudinal data; Data mining","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":[0.001002238,0.000160925,0.0001633121,0.00007013273,0.0001887259,0.00008369548,0.0001359755,0.00004326576,0.0000710886],"category_scores_gemma":[0.0001014228,0.0001638422,0.00000778895,0.001083018,0.0001160486,0.0008864045,0.0001794375,0.0003170896,0.000005742233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001092958,"about_ca_system_score_gemma":0.00002149165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001709121,"about_ca_topic_score_gemma":0.0001624378,"domain_scores_codex":[0.9983385,0.00008529153,0.0003706198,0.0005009362,0.0003071387,0.0003974836],"domain_scores_gemma":[0.9995573,0.00007937635,0.0001481766,0.0001225119,0.00001111584,0.00008147586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002399872,0.00001703081,0.7881946,0.00002391457,0.000008004272,0.00001079772,0.0104774,0.1759907,0.0007662507,0.000391309,0.00002589188,0.02407017],"study_design_scores_gemma":[0.0006631526,0.0001012471,0.1167112,0.0001326586,0.00001138621,0.000008158107,0.002190846,0.8778168,0.0004081741,0.001339652,0.0002401117,0.0003766387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9228561,0.00001261935,0.07386398,0.000695575,0.00004108015,0.0002012194,0.000003604782,0.00005549469,0.002270365],"genre_scores_gemma":[0.9849245,0.000003826688,0.01297056,0.001928344,0.00009322836,0.00001963832,0.00001906931,0.00002760738,0.00001323869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7018261,"threshold_uncertainty_score":0.6681292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05327658174441205,"score_gpt":0.269916452289791,"score_spread":0.2166398705453789,"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."}}