{"id":"W2532978152","doi":"10.1177/0033354916669358","title":"State Trauma Registries as a Resource for Occupational Injury Surveillance and Research","year":2016,"lang":"en","type":"article","venue":"Public Health Reports","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health","funders":"National Institute for Occupational Safety and Health","keywords":"Medicine; Workers' compensation; Occupational safety and health; Injury prevention; Occupational injury; Poison control; Concordance; Population; Compensation (psychology); Medical emergency; Suicide prevention; Human factors and ergonomics; Hospital discharge; External cause; Environmental health; Emergency medicine; Intensive care medicine; Psychology","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":[0.03735064,0.0007820648,0.001237216,0.01944297,0.001089056,0.003032766,0.003145312,0.000994656,0.006186182],"category_scores_gemma":[0.07586393,0.00154407,0.0009170093,0.02806183,0.0004206017,0.003381497,0.004244184,0.001848787,0.00266843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002481476,"about_ca_system_score_gemma":0.01851042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02478763,"about_ca_topic_score_gemma":0.02773466,"domain_scores_codex":[0.9614568,0.01739661,0.01145023,0.003254539,0.005630495,0.0008112945],"domain_scores_gemma":[0.795293,0.04041661,0.0642143,0.04576267,0.04890066,0.005412803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003632822,0.0005243892,0.4919662,0.002578755,0.001047483,0.0002631454,0.001272433,0.003638388,0.0009185302,0.009709082,0.2291313,0.258587],"study_design_scores_gemma":[0.0004887781,0.0006019953,0.5676508,0.005635739,0.001018522,0.0008936822,0.002644113,0.01139942,0.002249121,0.005798577,0.4013374,0.000281903],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1178461,0.01397323,0.1073434,0.01162516,0.001654326,0.0119441,0.6824527,0.004926297,0.04823467],"genre_scores_gemma":[0.230841,0.01108448,0.1660586,0.002377671,0.001255968,0.01610949,0.5637727,0.0006020589,0.007897947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03735064,"threshold_uncertainty_score":0.1975314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2856687858730142,"score_gpt":0.5605772247750362,"score_spread":0.274908438902022,"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."}}