{"id":"W4200320334","doi":"10.30978/unj2021-3-31","title":"Post-stroke cognitive impairment: screening with MMSE and MoCA and predictors of their persistence after treatment at the Stroke Center","year":2021,"lang":"en","type":"article","venue":"Ukrainian Neurological Journal","topic":"Neurological Disorders and Treatments","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Medicine; Logistic regression; Conventional PCI; Internal medicine; Stroke (engine); Cognitive impairment; Physical therapy; Mini–Mental State Examination; Cardiology; Disease; Myocardial infarction","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":[],"consensus_categories":[],"category_scores_codex":[0.00009366447,0.0002927082,0.0003064013,0.00004970786,0.0003983983,0.0001104774,0.0001196357,0.00008076595,0.0001781333],"category_scores_gemma":[0.0001628816,0.0001364929,0.0001511878,0.00009537674,0.0007540997,0.0001204319,0.000211718,0.0003446008,0.00000291625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001280391,"about_ca_system_score_gemma":0.00002815209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001973735,"about_ca_topic_score_gemma":0.00001389602,"domain_scores_codex":[0.9979734,0.0004767673,0.0002630558,0.000555081,0.0003052058,0.0004264769],"domain_scores_gemma":[0.9986888,0.0006445625,0.0001655878,0.0001624303,0.00007309671,0.000265591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009883007,0.002001232,0.9187972,0.00001917647,0.0002988298,0.009827217,0.005371324,0.00002322464,0.02841823,0.00001442714,0.00001128657,0.02533484],"study_design_scores_gemma":[0.009270901,0.02382218,0.9371595,0.00005526147,0.000291766,0.00978522,0.0008362141,0.0002334126,0.01645636,0.00007906669,0.001608199,0.000401852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955374,0.0004791339,0.000006956014,0.002677712,0.00006131972,0.0002674681,0.0004948445,0.00001878216,0.0004564062],"genre_scores_gemma":[0.9936217,0.0008282061,0.00003839262,0.005113933,0.00003790242,0.00002169663,0.000002760659,0.00001498967,0.0003203925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02493299,"threshold_uncertainty_score":0.5566021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02474218783517498,"score_gpt":0.2285134218426189,"score_spread":0.2037712340074439,"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."}}