{"id":"W2019386223","doi":"10.1111/ijs.12304","title":"Acute Imaging Does Not Improve ASTRAL Score's Accuracy despite Having a Prognostic Value","year":2014,"lang":"en","type":"article","venue":"International Journal of Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Schweizerische Herzstiftung; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Medicine; Magnetic resonance imaging; Computed tomography angiography; Radiology; Logistic regression; Magnetic resonance angiography; Odds ratio; Stroke (engine); Angiography; Modified Rankin Scale; Internal medicine; Ischemic stroke; Ischemia","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006286085,0.000789653,0.0009474303,0.001367578,0.00024994,0.001391907,0.0007694378,0.000798065,0.001857992],"category_scores_gemma":[0.03263061,0.0002642792,0.001270756,0.00131628,0.0006855734,0.001174182,0.0009682572,0.0007516569,0.001012973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003956317,"about_ca_system_score_gemma":0.0005683445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001750272,"about_ca_topic_score_gemma":0.002857902,"domain_scores_codex":[0.9954378,0.001949473,0.0006555059,0.0006378536,0.001009397,0.0003099722],"domain_scores_gemma":[0.9591299,0.02178144,0.01039162,0.003586416,0.003600172,0.001510417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006107538,0.0000208002,0.9873059,0.00003912938,0.0002019339,0.00005169421,0.0000413468,0.0007278599,0.0001318564,0.00005360981,0.0004121382,0.01040303],"study_design_scores_gemma":[0.00004349382,0.0007332421,0.9839828,0.00007327717,0.0004896257,0.000954255,0.00008694471,0.01131086,0.00050237,0.0005841678,0.001206708,0.00003224298],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868429,0.002784349,0.002706614,0.0009143814,0.0001029487,0.00002588792,0.001386169,0.0002164663,0.005020322],"genre_scores_gemma":[0.9983205,0.0001719908,0.0006623758,0.00005589356,0.00005349967,0.000003837218,0.0005820852,0.00001357079,0.0001360978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006286085,"threshold_uncertainty_score":0.03324437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009269585786571681,"score_gpt":0.2832228852367261,"score_spread":0.2739532994501544,"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."}}