{"id":"W2063646895","doi":"10.1159/000355024","title":"Magnetic Resonance Imaging versus Computed Tomography in Transient Ischemic Attack and Minor Stroke: The More &amp;#x03A5;ou See the More You Know","year":2013,"lang":"en","type":"article","venue":"Cerebrovascular Diseases Extra","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Calgary; Université de Sherbrooke","funders":"","keywords":"Medicine; Magnetic resonance imaging; Stroke (engine); Acute stroke; Computed tomography; Prospective cohort study; Radiology; Ischemia; Cardiology; Lesion; Nuclear medicine; Internal medicine; Surgery","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001799333,0.0004621274,0.0004510639,0.0001762957,0.0001784858,0.0001193888,0.0005014958,0.00008226155,0.0003485296],"category_scores_gemma":[0.00007449129,0.0003031909,0.0004635442,0.0005462379,0.0007096754,0.0001654163,0.000217641,0.0004151869,0.00005567708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009446498,"about_ca_system_score_gemma":0.00006555383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002069622,"about_ca_topic_score_gemma":0.00002577902,"domain_scores_codex":[0.9973068,0.0001042737,0.0004478477,0.0007541175,0.0007086757,0.0006782604],"domain_scores_gemma":[0.9979736,0.0001668727,0.00009619675,0.001352062,0.0001223418,0.0002889082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0007404183,0.0009085819,0.3616323,0.0008495926,0.001045924,0.000119925,0.002979404,0.0001569284,0.004107584,0.00006320306,0.4034179,0.2239783],"study_design_scores_gemma":[0.005577406,0.00007397637,0.6818382,0.0002605382,0.001006397,0.00004821513,0.001759865,0.003746311,0.0001359076,0.000004349721,0.3051603,0.0003885498],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8777949,0.1078676,0.0004019593,0.00867943,0.0002569301,0.002424372,0.00008106453,0.0001414766,0.002352243],"genre_scores_gemma":[0.9933281,0.001054209,0.001390147,0.001581484,0.0002919271,0.0004547105,0.0001672488,0.00009867719,0.001633493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.320206,"threshold_uncertainty_score":0.999942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01161903546227713,"score_gpt":0.2434640723543669,"score_spread":0.2318450368920898,"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."}}