{"id":"W4283028173","doi":"10.3389/fnagi.2022.834273","title":"Combined Functional Assessment for Predicting Clinical Outcomes in Stroke Patients After Post-acute Care: A Retrospective Multi-Center Cohort in Central Taiwan","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Taichung Veterans General Hospital; Ministry of Science and Technology, Taiwan","keywords":"Medicine; Activities of daily living; Logistic regression; Modified Rankin Scale; Montreal Cognitive Assessment; Physical therapy; Stroke (engine); Quality of life (healthcare); Cohort; Odds ratio; Acute care; Retrospective cohort study; Berg Balance Scale; Rehabilitation; Cohort study; Internal medicine; Disease; Cognitive impairment; Health care; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000934816,0.0004555842,0.0004751708,0.001230552,0.000600967,0.0008947768,0.000469015,0.0005070869,0.0007072466],"category_scores_gemma":[0.001937163,0.0003449832,0.000559183,0.00140811,0.0003816827,0.0006347637,0.0007756138,0.0005658274,0.0001818022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004992625,"about_ca_system_score_gemma":0.0006216312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007732585,"about_ca_topic_score_gemma":0.0104665,"domain_scores_codex":[0.9993205,0.0001444383,0.0001366487,0.0001964652,0.00009298243,0.0001089835],"domain_scores_gemma":[0.9987539,0.0001197673,0.0005186209,0.000147508,0.0001953314,0.0002647834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003891355,0.0000139784,0.9995446,0.00000262399,0.00002777401,0.0000528231,0.00002578328,0.00001074607,0.0000461455,0.000002162746,0.00002090321,0.0002136656],"study_design_scores_gemma":[0.000007331274,0.00007544841,0.999189,0.00000531608,0.00002644473,0.0002119689,0.0002213041,0.0001761542,0.00002581042,0.00000802164,0.00005003761,0.00000323192],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995592,0.0001048979,0.00004291709,0.00002042715,0.000002940718,0.00001071275,0.0001658447,0.000001581064,0.00009135873],"genre_scores_gemma":[0.9995838,0.00004346312,0.0000360123,0.00001374852,0.000005770949,0.00001454707,0.0002649119,8.204749e-7,0.00003705835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007732585,"threshold_uncertainty_score":0.01537514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01453139832025166,"score_gpt":0.3080540564055324,"score_spread":0.2935226580852808,"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."}}