{"id":"W3032881810","doi":"10.3760/cma.j.issn.1674-6554.2017.01.010","title":"Application of MoCA and MMSE in screening for cognitive impairment in acute ischemic stroke","year":2017,"lang":"en","type":"article","venue":"Zhonghua xingwei yixue yu naokexue zazhi","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Cognitive impairment; Medicine; Stroke (engine); Ischemic stroke; Cognition; Mini–Mental State Examination; Internal medicine; Physical therapy; Cardiology; Disease; Psychiatry; Ischemia","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000551992,0.0002921376,0.0006175977,0.00036715,0.0001225417,0.00004589813,0.0002793658,0.0001706037,0.0000130053],"category_scores_gemma":[0.0002913903,0.0003000739,0.000116538,0.0001323297,0.0001947776,0.0002520851,0.0003099794,0.000309904,0.000007505817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001314728,"about_ca_system_score_gemma":0.00005923912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003572965,"about_ca_topic_score_gemma":0.00007978711,"domain_scores_codex":[0.9980006,0.00002444198,0.0005910384,0.0005981236,0.0003108415,0.0004750113],"domain_scores_gemma":[0.9984844,0.0001644731,0.000454498,0.0006400002,0.000124688,0.0001319786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003987705,0.0008593499,0.702659,0.001149059,0.0007802545,0.0001788084,0.002120205,0.0000376,0.1655572,0.0002276927,0.006649881,0.1157932],"study_design_scores_gemma":[0.03216545,0.001233868,0.7590839,0.00205163,0.0009582075,0.0000968755,0.00279478,0.02304952,0.1649935,0.0001116069,0.01246942,0.0009912545],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768847,0.0003152346,0.01388121,0.001008797,0.000083246,0.002487392,0.0001191744,0.00004137726,0.005178902],"genre_scores_gemma":[0.9906037,0.00008957558,0.007184804,0.0002087231,0.0001139974,0.0004340646,0.00009124343,0.00005014431,0.001223704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.114802,"threshold_uncertainty_score":0.9999452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01676819936956814,"score_gpt":0.3030528392866056,"score_spread":0.2862846399170375,"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."}}