{"id":"W3087714085","doi":"10.1007/s41999-020-00393-0","title":"Impact of malnutrition on post-stroke cognitive impairment in convalescent rehabilitation ward inpatients","year":2020,"lang":"en","type":"article","venue":"European Geriatric Medicine","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Interquartile range; Medicine; Functional Independence Measure; Cognition; Rehabilitation; Univariate analysis; Malnutrition; Physical therapy; Multivariate analysis; Stroke (engine); Cohort; Modified Rankin Scale; Montreal Cognitive Assessment; Internal medicine; Cognitive impairment; Pediatrics; Psychiatry; Ischemic stroke","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":[0.0006228382,0.0001889566,0.0004842899,0.0004304637,0.00003428986,0.000003444827,0.00006461271,0.00004115399,0.0004335683],"category_scores_gemma":[0.001079537,0.0001495586,0.0001288732,0.0004820077,0.0000971484,0.00005024986,0.0000292325,0.0002974471,0.0001091769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002114229,"about_ca_system_score_gemma":0.00009022355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004817753,"about_ca_topic_score_gemma":7.678306e-7,"domain_scores_codex":[0.9977736,0.0003858382,0.000791953,0.0003304062,0.0004569124,0.000261239],"domain_scores_gemma":[0.9986788,0.0002472469,0.0002580453,0.0001524047,0.0002987552,0.0003647225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02577893,0.004698549,0.8637776,0.00509178,0.0001911514,0.000596888,0.02153552,0.00003234917,0.03168763,0.0001037962,0.02024795,0.02625783],"study_design_scores_gemma":[0.01795119,0.02225141,0.9560468,0.00179209,0.00007858136,0.00001534419,0.001011301,0.0001540536,0.0002326781,0.00001179388,0.000323687,0.0001310941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841384,0.0002532678,0.0000584063,0.01030611,0.0001662303,0.001248236,0.00007893192,0.00005332114,0.003697107],"genre_scores_gemma":[0.9954785,0.0002065161,0.0003780126,0.003141431,0.0004980827,0.00001149366,0.0002056779,0.00003253029,0.00004776269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09226915,"threshold_uncertainty_score":0.6098822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03190575052049214,"score_gpt":0.3306794158749281,"score_spread":0.2987736653544359,"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."}}