{"id":"W4224250150","doi":"10.1371/journal.pone.0265509","title":"Identifying the changing age distribution of opioid-related mortality with high-frequency data","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; Institute for Clinical Evaluative Sciences; St. Michael's Hospital; Women's College Hospital; Office of the Chief Medical Examiner; University of Toronto; Public Health Ontario","funders":"","keywords":"Demography; Medicine; Poisson regression; Mortality rate; Coroner; Population; Confidence interval; Injury prevention; Poison control; Medical emergency; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004071959,0.0002962273,0.0003087378,0.002158888,0.0004375612,0.0008681179,0.001009253,0.000510201,0.001183778],"category_scores_gemma":[0.01560605,0.0002866348,0.0004709344,0.002424868,0.0004184401,0.0006231415,0.0007532911,0.0004679477,0.0004368946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004100161,"about_ca_system_score_gemma":0.003576343,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6022305,"about_ca_topic_score_gemma":0.6614849,"domain_scores_codex":[0.9985651,0.0003651266,0.0001263408,0.0002885723,0.0004326346,0.0002222521],"domain_scores_gemma":[0.9916215,0.001989338,0.00300944,0.000769221,0.002336742,0.0002738333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003813809,0.00001013325,0.9880586,0.00005159605,0.00004433289,0.00005777056,0.0002508757,0.002544569,0.0002203443,0.0002649176,0.001251496,0.00720721],"study_design_scores_gemma":[0.000008798343,0.00002604693,0.9788551,0.00006377936,0.00003988794,0.0001198101,0.0004353294,0.0154957,0.0001982662,0.0005339626,0.004204391,0.00001895497],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.953746,0.0009568949,0.02123819,0.001118232,0.00003148544,0.0001422699,0.01917913,0.0001799929,0.00340775],"genre_scores_gemma":[0.9839585,0.0004433538,0.005915693,0.0001268317,0.000027536,0.00007000144,0.008670333,0.00001909441,0.000768668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6022305,"threshold_uncertainty_score":0.8002241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07725859492623575,"score_gpt":0.2856756216357292,"score_spread":0.2084170267094934,"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."}}