{"id":"W1802584573","doi":"10.5853/jos.2015.17.3.221","title":"Choosing a Hyperacute Stroke Imaging Protocol for Proper Patient Selection and Time Efficient Endovascular Treatment: Lessons from Recent Trials","year":2015,"lang":"en","type":"review","venue":"Journal of Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Magnetic resonance imaging; Endovascular treatment; Randomized controlled trial; Radiology; Stroke (engine); Angiography; Magnetic resonance angiography; Clinical trial; Inclusion and exclusion criteria; Surgery; Internal medicine","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":[0.001850326,0.0007271261,0.004297412,0.0005816983,0.0001237769,0.0001344927,0.0001763305,0.0002221371,0.00009937991],"category_scores_gemma":[0.0005665952,0.0004473282,0.001457858,0.0001920888,0.0000488663,0.0001207033,0.0001065472,0.0005366522,0.0000137599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001765689,"about_ca_system_score_gemma":0.001013632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001390438,"about_ca_topic_score_gemma":3.821588e-7,"domain_scores_codex":[0.9952639,0.0004309865,0.002345496,0.0005591994,0.000919641,0.0004807632],"domain_scores_gemma":[0.9952793,0.0003224987,0.002904992,0.0003723722,0.0007339987,0.000386806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000694927,0.0004957581,0.00001180588,0.002015476,0.003492353,0.00008522951,0.0001154343,0.000009129412,0.0003062164,0.000001264581,0.00750892,0.9852635],"study_design_scores_gemma":[0.008807111,0.001539629,0.000002605198,0.009954571,0.01138818,0.0007613553,0.00007050713,0.0003122028,0.0003915827,0.000002178867,0.9664508,0.0003193155],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000128111,0.8089196,0.001181412,0.0005198526,0.0003847859,0.1874566,0.0005234017,0.00004584494,0.0008404299],"genre_scores_gemma":[0.000007040231,0.8982452,0.01993209,0.00008922462,0.002359413,0.07748913,0.0001459152,0.000221832,0.001510174],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9849442,"threshold_uncertainty_score":0.9997978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138068924989123,"score_gpt":0.4024348794068277,"score_spread":0.2886279869079154,"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."}}