{"id":"W2301716034","doi":"10.1201/b13186-24","title":"Drowning and Near Drowning","year":2008,"lang":"en","type":"article","venue":"","topic":"Injury Epidemiology and Prevention","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Near Drowning; Medical emergency; Forensic engineering; Engineering; Medicine; Poison control; Suicide prevention","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002155427,0.0002834563,0.0003152466,0.0009475274,0.0009763057,0.001228654,0.0004041265,0.0007068231,0.01663213],"category_scores_gemma":[0.002456759,0.00009216379,0.0003171621,0.0008037845,0.0007357955,0.001208705,0.001455679,0.0007739869,0.002500484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000524116,"about_ca_system_score_gemma":0.0005169159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006423107,"about_ca_topic_score_gemma":0.008768712,"domain_scores_codex":[0.9994261,0.00008233607,0.00005408292,0.00007246465,0.0002458539,0.0001190692],"domain_scores_gemma":[0.9991799,0.00008957819,0.0003011552,0.00005663284,0.0001842244,0.0001884446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004984814,0.0002615526,0.4617331,0.001589953,0.0001639157,0.02012856,0.004621165,0.000790814,0.002512641,0.02352552,0.059479,0.4246954],"study_design_scores_gemma":[0.00002662317,0.0004840368,0.4490589,0.003157164,0.0001093512,0.1400015,0.01276303,0.0006950183,0.001180447,0.01959569,0.3728184,0.0001098153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4873346,0.08295655,0.005146346,0.007096568,0.002783667,0.0003667696,0.004448445,0.0001429172,0.4097241],"genre_scores_gemma":[0.9371655,0.02834341,0.00129386,0.00201738,0.0008762437,0.00006197168,0.002343087,0.00003805503,0.02786053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01663213,"threshold_uncertainty_score":0.05564004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03600324195003179,"score_gpt":0.3162490094068517,"score_spread":0.2802457674568199,"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."}}