{"id":"W4389208232","doi":"10.1007/s12561-023-09407-4","title":"Evaluating Effects of Various Exposures on Mortality Risk of Opioid Use Disorders with Linked Administrative Databases","year":2023,"lang":"en","type":"article","venue":"Statistics in Biosciences","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for Advancing Health Outcomes; St. Paul's Hospital; Simon Fraser University","funders":"National Institute of Nursing Research; Natural Sciences and Engineering Research Council of Canada","keywords":"Biostatistics; Covariate; Medicine; Hazard; Proportional hazards model; Data mining; Econometrics; Actuarial science; Computer science; Statistics; Public health; Machine learning; Business; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002636761,0.0001697006,0.0003068331,0.000325972,0.0003637108,0.00006191286,0.000433018,0.00004404436,0.00001266197],"category_scores_gemma":[0.003722847,0.0001391921,0.00004494813,0.00181609,0.002231962,0.0002406639,0.0000794842,0.0001483731,0.000002649586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003503048,"about_ca_system_score_gemma":0.0003093546,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01944971,"about_ca_topic_score_gemma":0.07045671,"domain_scores_codex":[0.9965315,0.0007303624,0.0004690096,0.000448617,0.001418348,0.0004021763],"domain_scores_gemma":[0.9962424,0.00267821,0.0005101118,0.0003382505,0.0001562747,0.00007473324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004077392,0.0002237119,0.9215611,0.0001743847,0.00004947501,0.000014793,0.007938111,0.0005674975,0.00008678521,0.06513088,0.000097895,0.004114587],"study_design_scores_gemma":[0.0003282763,0.0007571192,0.9819929,0.0001489266,0.0000621788,4.681407e-8,0.004633553,0.0008213628,0.0003564618,0.01064412,0.00007331058,0.0001817709],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950038,0.00003852303,0.001779662,0.00002673765,0.000443494,0.0008040328,0.0008988571,0.00004694327,0.0009579707],"genre_scores_gemma":[0.9872441,0.0009376021,0.01165209,0.00001825919,0.00002242569,0.00004565105,0.00002967984,0.000008466282,0.00004169598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06043177,"threshold_uncertainty_score":0.9870799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09982524946763711,"score_gpt":0.4270462260048003,"score_spread":0.3272209765371632,"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."}}