{"id":"W2982353732","doi":"10.1017/cjn.2019.319","title":"Temporal Trends in the Unmet Health Care Needs of Canadian Stroke Survivors","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Toronto","funders":"","keywords":"Stroke (engine); Medicine; Health care; Population; Gerontology; Needs assessment; Epidemiology; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.002178285,0.0004034612,0.0005635698,0.003777546,0.001724383,0.001233138,0.00178285,0.0005126662,0.002760574],"category_scores_gemma":[0.007161435,0.0003394249,0.001202299,0.00699928,0.0004956047,0.0007480793,0.001136786,0.001049772,0.0001922609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02779673,"about_ca_system_score_gemma":0.0376891,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9928316,"about_ca_topic_score_gemma":0.9934719,"domain_scores_codex":[0.997629,0.0001574493,0.0001976788,0.0002702861,0.001062814,0.0006828149],"domain_scores_gemma":[0.9946419,0.0003495121,0.0010484,0.0001290898,0.003284784,0.0005463118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001375705,0.00002586267,0.9787634,0.0002305264,0.0002739232,0.00007799639,0.001176634,0.0003755801,0.0001359706,0.0003846662,0.005854738,0.01256316],"study_design_scores_gemma":[0.000003797197,0.000009759689,0.9973283,0.0000518935,0.00004059563,0.0000324392,0.0007490258,0.0003681773,0.00003541189,0.00003213155,0.001334539,0.0000139519],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9392169,0.004587787,0.0004833836,0.003251602,0.00005654408,0.0001034268,0.04525883,0.00006948855,0.006972052],"genre_scores_gemma":[0.9861645,0.001804327,0.0005351795,0.000249235,0.00001409534,0.00006365522,0.01025167,0.00001165001,0.0009056313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02779673,"threshold_uncertainty_score":0.2016804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03285280336632906,"score_gpt":0.283157976730631,"score_spread":0.2503051733643019,"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."}}