{"id":"W4410691941","doi":"10.3390/urbansci9060185","title":"Urban Air and Emergency Department Visits in Toronto, Canada","year":2025,"lang":"en","type":"article","venue":"Urban Science","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Emergency department; Medical emergency; Geography; Emergency medicine; Medicine; Nursing","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":[0.0003082793,0.0002991625,0.0002479907,0.0008881188,0.001649302,0.0008969914,0.0007449023,0.0002452439,0.004492706],"category_scores_gemma":[0.001524747,0.0002127597,0.000418995,0.00299491,0.0004112282,0.0003240538,0.0007722483,0.0005151213,0.0002080965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02802605,"about_ca_system_score_gemma":0.03504288,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958156,"about_ca_topic_score_gemma":0.9979339,"domain_scores_codex":[0.9992377,0.00007372659,0.00004995337,0.0001032576,0.0003126233,0.0002229423],"domain_scores_gemma":[0.9985678,0.0001078421,0.0003333435,0.00002929717,0.0005026885,0.0004589987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001061559,0.0000430872,0.9770138,0.0001804317,0.00009239784,0.0003287373,0.001466607,0.0007033642,0.000310945,0.0004997529,0.008007413,0.01124732],"study_design_scores_gemma":[0.000005325137,0.00002033414,0.9956294,0.00004278107,0.00002049247,0.00006327193,0.001378833,0.0003761711,0.00005109151,0.00003549694,0.002366783,0.00001005592],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9546968,0.003854657,0.0006360855,0.001779508,0.0001003306,0.0001330176,0.02383292,0.00007304627,0.01489357],"genre_scores_gemma":[0.9898412,0.00167486,0.0003580994,0.0001821466,0.00002400497,0.00003097693,0.003808211,0.000008487817,0.004072136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02802605,"threshold_uncertainty_score":0.2033442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01451938564715727,"score_gpt":0.2905693464009161,"score_spread":0.2760499607537588,"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."}}