{"id":"W3025021800","doi":"10.1017/cem.2020.230","title":"P022: Use of police and SAR records to identify cases and reduce survivorship bias in prehospital care research","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Coroner; Medicine; Medical record; Medical emergency; Health records; Retrospective cohort study; Population; Vital signs; Health care; Poison control; Emergency medicine; Injury prevention; Family medicine; Environmental health","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.106664,0.0007202884,0.000775636,0.002259145,0.002317614,0.003050991,0.003566249,0.003182674,0.007566062],"category_scores_gemma":[0.3736183,0.0009796171,0.002314314,0.005291943,0.001407543,0.004477445,0.002786225,0.001567929,0.001023967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009996636,"about_ca_system_score_gemma":0.006717728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01348383,"about_ca_topic_score_gemma":0.02892119,"domain_scores_codex":[0.8215148,0.1361074,0.01818778,0.007018848,0.01497083,0.002200488],"domain_scores_gemma":[0.6792501,0.2130796,0.03421178,0.03571516,0.03327135,0.004471907],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003001862,0.0006152439,0.8273128,0.003485341,0.005641061,0.00054303,0.005179472,0.000541126,0.0007677069,0.003734241,0.0395505,0.1096275],"study_design_scores_gemma":[0.001435111,0.002320528,0.9233443,0.002061222,0.004710375,0.001080281,0.003929045,0.006506576,0.003493892,0.007317093,0.04365445,0.0001471773],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8052797,0.006489971,0.06278079,0.03230258,0.004030956,0.0133485,0.02360966,0.0005225731,0.05163538],"genre_scores_gemma":[0.9275095,0.0005602994,0.04970537,0.00474906,0.0009426506,0.008348678,0.003559242,0.000132564,0.0044927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8933361,"threshold_uncertainty_score":0.5640997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.511477822763018,"score_gpt":0.4744748513169768,"score_spread":0.0370029714460412,"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."}}