{"id":"W4413834861","doi":"10.24908/iqurcp18984","title":"Informing Community Coalitions Through the Use of Existing Databases to Inform Drowning Prevention Action","year":2025,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Injury Epidemiology and Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Action (physics); Database; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.02236163,0.0005412266,0.0006872113,0.01598284,0.001262853,0.003628275,0.002355956,0.0009925634,0.006664413],"category_scores_gemma":[0.08218651,0.0005361767,0.0006432229,0.009397728,0.0004073938,0.004089132,0.006094809,0.001431062,0.001225764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00237489,"about_ca_system_score_gemma":0.01103772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05128942,"about_ca_topic_score_gemma":0.07433287,"domain_scores_codex":[0.983704,0.008347009,0.003705716,0.001427251,0.002052783,0.0007631549],"domain_scores_gemma":[0.92702,0.03012629,0.01621095,0.00783369,0.01341514,0.005393812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003583214,0.0008288437,0.6359352,0.003375658,0.0004478467,0.0004951531,0.01051193,0.001199054,0.000531646,0.004706252,0.09602357,0.2455865],"study_design_scores_gemma":[0.0004162284,0.0005662902,0.5705504,0.01786391,0.0007070566,0.0004699661,0.05308749,0.01347903,0.001864997,0.01164044,0.3290958,0.0002584329],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5976602,0.01027848,0.03538645,0.04270641,0.0007202401,0.01411646,0.2183592,0.001191589,0.07958095],"genre_scores_gemma":[0.79623,0.008985672,0.07484753,0.004855848,0.0003190092,0.01306997,0.09791797,0.0001259689,0.003647966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05128942,"threshold_uncertainty_score":0.118261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6376322684707538,"score_gpt":0.543651655359447,"score_spread":0.09398061311130679,"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."}}