{"id":"W3026001727","doi":"10.1017/cem.2020.152","title":"MP04: Predicting future ED needs – population trends may not be enough!","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Demography; Medicine; Population; Per capita; Census; Trend analysis; Cohort; Gerontology; Environmental health; Statistics; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.008067191,0.001078656,0.001102796,0.002111025,0.00136561,0.003735111,0.002094852,0.002078498,0.02406313],"category_scores_gemma":[0.04755143,0.0006022298,0.001616355,0.002327773,0.0004311146,0.00485881,0.003066586,0.003810144,0.00650336],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002042083,"about_ca_system_score_gemma":0.006106373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1045659,"about_ca_topic_score_gemma":0.1785037,"domain_scores_codex":[0.9966731,0.001124559,0.000449698,0.0003799978,0.0009238531,0.0004487786],"domain_scores_gemma":[0.9806694,0.006076511,0.001685763,0.001120881,0.00702449,0.003422988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002901652,0.0001807566,0.248898,0.0004795889,0.000312317,0.0001278189,0.0002493256,0.0008990307,0.00008431878,0.001830005,0.5731844,0.1734644],"study_design_scores_gemma":[0.0004816971,0.0007962622,0.5167036,0.005905624,0.001310925,0.0009172281,0.003336655,0.01917933,0.0009337382,0.02130301,0.428744,0.0003878948],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1253924,0.01210892,0.01231761,0.6633655,0.01214371,0.0004593755,0.09856884,0.003352305,0.07229131],"genre_scores_gemma":[0.642667,0.01211755,0.07493319,0.1345718,0.01304262,0.001776437,0.08226656,0.001359092,0.03726572],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9979579,"threshold_uncertainty_score":0.2079145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1162690917003635,"score_gpt":0.3845049877307055,"score_spread":0.268235896030342,"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."}}