{"id":"W2588655222","doi":"10.1159/000457810","title":"MRI-Based Neuroanatomical Predictors of Dysphagia, Dysarthria, and Aphasia in Patients with First Acute Ischemic Stroke","year":2017,"lang":"en","type":"article","venue":"Cerebrovascular Diseases Extra","topic":"Dysphagia Assessment and Management","field":"Health Professions","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Krembil Foundation; McMaster University; Toronto Rehabilitation Institute; University Health Network; Toronto General Hospital; University of Toronto; Toronto Western Hospital; University of Ottawa","funders":"Ontario Ministry of Health and Long-Term Care; Canadian Stroke Network; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"Medicine; Dysarthria; Dysphagia; Stroke (engine); Odds ratio; Internal medicine; Atrophy; Aphasia; Cardiology; Confidence interval; Hyperintensity; Magnetic resonance imaging; Gastroenterology; Surgery; Radiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001913416,0.0003007917,0.0004935563,0.0001667192,0.0005615338,0.00004415555,0.0004605408,0.0001336339,0.0002497307],"category_scores_gemma":[0.0001026593,0.0002551154,0.0001448405,0.00009202291,0.000269657,0.0003722755,0.0002627833,0.0003214506,0.0000180655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008306218,"about_ca_system_score_gemma":0.0002352672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001205454,"about_ca_topic_score_gemma":0.0002322254,"domain_scores_codex":[0.997708,0.0001517358,0.0005039398,0.0005471979,0.0005315965,0.0005575512],"domain_scores_gemma":[0.9979354,0.0001354637,0.0004061274,0.001102635,0.000117261,0.0003031246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002885226,0.0004348273,0.9946548,0.0004267954,0.0004601279,0.00001670295,0.00008483807,0.00002028677,0.000009523658,0.00009754443,0.002707179,0.0007988169],"study_design_scores_gemma":[0.009879287,0.0001797999,0.9834211,0.0002764672,0.0005891116,1.789725e-7,0.00007918768,0.0003312516,0.00003430519,0.00001771016,0.004940516,0.0002510809],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99512,0.0002561694,0.0004157625,0.0002938727,0.0003610967,0.001640486,0.0001970572,0.00006749428,0.001648],"genre_scores_gemma":[0.9987059,0.0001203316,0.0002806145,0.0001438841,0.00006137441,0.0001775755,0.0001345718,0.00005186501,0.000323902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01123373,"threshold_uncertainty_score":0.9999901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008652876188513056,"score_gpt":0.2838166146132051,"score_spread":0.275163738424692,"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."}}