{"id":"W2003641432","doi":"10.1371/journal.pone.0030336","title":"Factors Associated with Physician Agreement on Verbal Autopsy of over 11500 Injury Deaths in India","year":2012,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Injury Epidemiology and Prevention","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Public Health Ontario; Hospital for Sick Children; Centre for Global Health Research; SickKids Foundation; University of Toronto; St. Michael's Hospital","funders":"","keywords":"Medicine; Verbal autopsy; Injury prevention; Poison control; Respondent; Cause of death; Cohen's kappa; Autopsy; External cause; Occupational safety and health; Multivariate analysis; Logistic regression; Suicide prevention; Kappa; Emergency medicine; Demography; Medical emergency; Internal medicine; Pathology; Disease","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":[0.0003948337,0.0001161509,0.0003723397,0.00009450705,0.00002433295,0.000001112339,0.00004064056,0.0001306689,0.0001850749],"category_scores_gemma":[0.0001728064,0.00008762171,0.00004801871,0.0001489379,0.0000393273,0.00007624493,0.00001451113,0.0002385758,0.00002024768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001167172,"about_ca_system_score_gemma":0.00002989183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002070132,"about_ca_topic_score_gemma":0.00000734306,"domain_scores_codex":[0.9990385,0.0001443243,0.0002234012,0.0001193489,0.0002220844,0.000252315],"domain_scores_gemma":[0.9994665,0.0001321724,0.0001491219,0.0001565592,0.00003244879,0.00006314486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003338066,0.00374868,0.9852619,0.00005013286,0.0004145161,0.000001432064,0.0005469244,4.896998e-7,0.008473119,0.0006701859,0.0001702587,0.0003286223],"study_design_scores_gemma":[0.0007647127,0.0008380464,0.9629545,0.0005652796,0.0002054958,6.56371e-8,0.00004400272,0.00001401841,0.03440579,0.0001036138,0.00001886531,0.00008559495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993758,0.00004540644,0.000003336873,0.00006121676,0.00004606507,0.0002767356,0.00002279813,0.00002035287,0.005766149],"genre_scores_gemma":[0.999007,0.000006119765,0.00005581617,0.0003983444,0.00007937481,0.00001270664,0.000101203,0.00001114833,0.0003282653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02593267,"threshold_uncertainty_score":0.357311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06812949459091211,"score_gpt":0.3006284267671953,"score_spread":0.2324989321762832,"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."}}