{"id":"W3029803082","doi":"10.1080/10920277.2020.1737495","title":"Advances in Predictive Analytics","year":2020,"lang":"en","type":"article","venue":"North American Actuarial Journal","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Predictive analytics; Analytics; Data science; Computer science; Range (aeronautics); Predictive value; Engineering; Medicine; Internal 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":[0.01112144,0.001663745,0.001763743,0.007017681,0.001144132,0.00904083,0.002054201,0.002790296,0.01453704],"category_scores_gemma":[0.05061328,0.0008048536,0.001639398,0.00741093,0.002621443,0.0105194,0.003972236,0.00954766,0.00851084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001824975,"about_ca_system_score_gemma":0.003646418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001755956,"about_ca_topic_score_gemma":0.001557164,"domain_scores_codex":[0.9907302,0.001929051,0.0007419111,0.001165068,0.005040018,0.0003937923],"domain_scores_gemma":[0.9350554,0.04707549,0.001708202,0.003739267,0.01043132,0.001990323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005718815,0.00008045701,0.001386886,0.001320221,0.0001653226,0.0001247264,0.0001915002,0.002530494,0.0003462124,0.06474831,0.5285087,0.4005399],"study_design_scores_gemma":[0.00001449383,0.00004929023,0.0009717579,0.001253094,0.00005487427,0.0003565033,0.0001578274,0.007577592,0.0003468101,0.1109311,0.8782209,0.00006580995],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002194194,0.5852568,0.1144844,0.1126876,0.1305544,0.000130891,0.001912603,0.00264201,0.050137],"genre_scores_gemma":[0.03007197,0.6156511,0.05427273,0.01839294,0.2522119,0.0001328798,0.00281692,0.001050862,0.02539869],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01453704,"threshold_uncertainty_score":0.05881649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01748064062144019,"score_gpt":0.2985119088576981,"score_spread":0.281031268236258,"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."}}