{"id":"W2535326255","doi":"10.1159/000449288","title":"How Reliable Are Administrative Data for Capturing Stroke Patients and Their Care","year":2016,"lang":"en","type":"article","venue":"Cerebrovascular Diseases Extra","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Stroke Network; University Health Network; Institute for Work & Health; Institute for Clinical Evaluative Sciences","funders":"Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences; Ontario Stroke Network; Heart and Stroke Foundation of Canada","keywords":"Medicine; Stroke (engine); Atrial fibrillation; Emergency medicine; Audit; Intracerebral hemorrhage; Medical record; Kappa; Population; Internal medicine; Medical emergency; Subarachnoid hemorrhage","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0000582196,0.000277738,0.0003681665,0.00006592775,0.0001059478,0.00006139807,0.000289043,0.00007280792,0.00003007317],"category_scores_gemma":[0.0003117019,0.0001747243,0.0001853289,0.00005489915,0.0001442245,0.0002822179,0.0003277774,0.00006705579,0.000004698151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001051331,"about_ca_system_score_gemma":0.00007490456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006911693,"about_ca_topic_score_gemma":0.000006452761,"domain_scores_codex":[0.9984497,0.00002086987,0.0001796188,0.000721996,0.0002691753,0.0003585887],"domain_scores_gemma":[0.9980711,0.00008098953,0.000116862,0.001250158,0.0001864218,0.0002944932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006532797,0.0006766929,0.811105,0.002376069,0.003092418,0.00003795648,0.0007858719,0.000001065862,0.002194988,0.0001963583,0.09324151,0.08563884],"study_design_scores_gemma":[0.01980465,0.000786893,0.4006242,0.001329312,0.002908004,0.00001713075,0.01588121,0.0001227532,0.01168892,0.00006746568,0.5457036,0.00106584],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9606792,0.01077447,0.01034567,0.002625199,0.0003440532,0.003579589,0.009756764,0.0002428514,0.001652246],"genre_scores_gemma":[0.9952256,0.0002129822,0.00110617,0.0001832982,0.000211632,0.0001277206,0.0009078574,0.0000536474,0.00197106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4524621,"threshold_uncertainty_score":0.7125049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0299097731534595,"score_gpt":0.2557872979193392,"score_spread":0.2258775247658797,"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."}}