{"id":"W2117422191","doi":"10.1136/ip.2008.018374","title":"Examining the sensitivity of an injury surveillance program using population-based estimates","year":2008,"lang":"en","type":"article","venue":"Injury Prevention","topic":"Injury Epidemiology and Prevention","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; University of Ottawa; University of Calgary; Children's Hospital of Eastern Ontario; York University","funders":"","keywords":"Representativeness heuristic; Injury prevention; Population; Poison control; Injury surveillance; Occupational safety and health; Medicine; Medical emergency; Suicide prevention; Human factors and ergonomics; Emergency medicine; Environmental health; Statistics; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002429281,0.0001540005,0.0003466316,0.0001051961,0.0002548365,0.000006041776,0.00005803895,0.0001624175,0.00005025394],"category_scores_gemma":[0.000532139,0.0001220563,0.0001317802,0.0002390618,0.0001378642,0.0001932121,0.00002232165,0.0002138032,0.000004595175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005371474,"about_ca_system_score_gemma":0.0001081952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002540401,"about_ca_topic_score_gemma":0.00003455437,"domain_scores_codex":[0.9978643,0.0009735965,0.0004851795,0.0002658783,0.0001977273,0.0002133086],"domain_scores_gemma":[0.9987599,0.0003109864,0.0003503493,0.0003825195,0.0001396702,0.00005655806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006925149,0.0004789139,0.905409,0.0001070584,0.00006485442,0.00001092638,0.00007106244,0.0004424972,0.02603922,0.00008534068,0.00006557617,0.06653309],"study_design_scores_gemma":[0.0003298457,0.0009246169,0.9513779,0.000155011,0.00008709692,0.00007781712,0.00001713341,0.03665799,0.009469329,0.0007254558,0.00004873478,0.0001290719],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928284,0.0000526991,0.005884289,0.00008109411,0.0002014176,0.0007230088,0.00001771863,0.0001246688,0.00008673656],"genre_scores_gemma":[0.9843369,0.00000763429,0.0150688,0.00009187288,0.0001246147,0.00002797487,0.0002570435,0.00001876778,0.00006646979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06640401,"threshold_uncertainty_score":0.4977313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06752273629902548,"score_gpt":0.3810245092358464,"score_spread":0.3135017729368209,"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."}}