{"id":"W2064670991","doi":"10.1159/000071121","title":"Computed Tomographic Parameters Predicting Fatal Outcome in Large Middle Cerebral Artery Infarction","year":2003,"lang":"en","type":"article","venue":"Cerebrovascular Diseases","topic":"Intracranial Aneurysms: Treatment and Complications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Medicine; Middle cerebral artery; Computed tomographic; Infarction; Cardiology; Stroke (engine); Cerebral infarction; Radiology; Computed tomographic angiography; Brain infarction; Computed tomography; Internal medicine; Ischemia; Myocardial infarction; Angiography","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001117471,0.0002434131,0.0003613064,0.0002779386,0.0001661837,0.00004489842,0.00009546892,0.00008993707,0.000164892],"category_scores_gemma":[0.0001140395,0.0002234032,0.0004183991,0.0005331921,0.00006981608,0.0001646936,0.00002890541,0.00019553,0.00006174321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008161701,"about_ca_system_score_gemma":0.00006157089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006274196,"about_ca_topic_score_gemma":0.00004199059,"domain_scores_codex":[0.9983127,0.0001154396,0.0004018257,0.0004366685,0.0002948621,0.0004384872],"domain_scores_gemma":[0.9990743,0.00005997177,0.00007799969,0.0004833619,0.0000736681,0.0002306623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004269779,0.0009195184,0.9965684,0.00009560357,0.0002132234,0.00003590872,0.00008095377,0.00004574038,0.00006022532,0.001407516,0.00005791732,0.0004722743],"study_design_scores_gemma":[0.003396462,0.0001419006,0.9929376,0.00008253667,0.0004518005,0.0001535831,0.0001949154,0.001305211,0.0001328025,0.0005320334,0.0004385442,0.0002325943],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967735,0.000506534,0.0006444426,0.0002332559,0.0001894173,0.0006584206,0.00004856173,0.0001992547,0.0007465518],"genre_scores_gemma":[0.9983529,0.00001736441,0.000614985,0.0003710438,0.00007591519,0.0001086042,0.0003332032,0.00002710051,0.00009888104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003630805,"threshold_uncertainty_score":0.9110118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0210182433549737,"score_gpt":0.2439008395000153,"score_spread":0.2228825961450416,"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."}}