{"id":"W2744971306","doi":"10.1161/str.47.suppl_1.wp141","title":"Abstract WP141: Identifying Modifiable Predictors of Long-term Functional Outcome After Stroke","year":2016,"lang":"en","type":"article","venue":"Stroke","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Stroke (engine); Montreal Cognitive Assessment; Depression (economics); Physical therapy; Modified Rankin Scale; Logistic regression; Sleep apnea; Stroke recovery; Internal medicine; Cognitive impairment; Ischemic stroke; Rehabilitation; Disease","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.002704126,0.001128482,0.0008811195,0.001940257,0.0005751572,0.00136486,0.001152865,0.0008780248,0.007879454],"category_scores_gemma":[0.008536385,0.0003400074,0.001265023,0.002123954,0.0003379202,0.0008962938,0.001245115,0.001096191,0.001949619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003740186,"about_ca_system_score_gemma":0.001497163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005774908,"about_ca_topic_score_gemma":0.004486815,"domain_scores_codex":[0.9991048,0.0002956274,0.0001127711,0.0001570946,0.0002024616,0.000127223],"domain_scores_gemma":[0.9963763,0.001306924,0.00111898,0.0002182777,0.0004225306,0.0005570106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005938574,0.0001504012,0.9846922,0.000142012,0.0004170969,0.00008494794,0.00004553792,0.0003941601,0.0001621058,0.00004019581,0.002514272,0.01076331],"study_design_scores_gemma":[0.00003922383,0.0002537944,0.9975425,0.00004039054,0.000219875,0.00007841404,0.00005964703,0.0008848509,0.000133709,0.0001114725,0.000627152,0.000008927507],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9695041,0.00176092,0.00168792,0.001464838,0.0001236547,0.0002542002,0.02263609,0.0001573561,0.002410879],"genre_scores_gemma":[0.9813136,0.0006478763,0.002133033,0.0001377848,0.0001607857,0.0004341411,0.01269804,0.0000409155,0.002433931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007879454,"threshold_uncertainty_score":0.02635944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03116127069759892,"score_gpt":0.2931330632445969,"score_spread":0.2619717925469979,"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."}}