{"id":"W2152955764","doi":"10.1161/strokeaha.111.000127","title":"Magnetic Resonance Imaging-DRAGON Score","year":2013,"lang":"en","type":"article","venue":"Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Magnetic resonance imaging; Middle cerebral artery; Modified Rankin Scale; Confidence interval; Stroke (engine); Radiology; Thrombolysis; Internal carotid artery; Computed tomography angiography; Magnetic resonance angiography; Angiography; Nuclear medicine; Ischemia; Internal medicine; Ischemic stroke","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":[0.0005579115,0.0005859442,0.0005270836,0.001946854,0.0002497437,0.0004602837,0.0003547682,0.0003183833,0.00210123],"category_scores_gemma":[0.003051446,0.00009588711,0.0003012929,0.0007478285,0.0002879874,0.0003074358,0.0005712604,0.0002605474,0.0004252086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000428576,"about_ca_system_score_gemma":0.0004597545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001923506,"about_ca_topic_score_gemma":0.002458504,"domain_scores_codex":[0.9995164,0.00008163214,0.00008898311,0.0001090464,0.000133668,0.00007021819],"domain_scores_gemma":[0.9986289,0.000196921,0.0006499769,0.00006704309,0.0002136746,0.0002435809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001535416,0.00002872969,0.9939891,0.00002583583,0.00005843939,0.0001893799,0.00002385914,0.0001827683,0.0001602627,0.0000389346,0.0006594406,0.004489873],"study_design_scores_gemma":[0.00002661497,0.0001732275,0.9959524,0.00001890992,0.00005201114,0.002115911,0.00002673961,0.0004633512,0.0001611009,0.00008294703,0.0009185384,0.000008276249],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926886,0.0006552209,0.0005427951,0.0001291103,0.00003465204,0.0001212469,0.001287876,0.00002709763,0.004513371],"genre_scores_gemma":[0.9964942,0.0001782297,0.0007478746,0.0000445412,0.00004750837,0.00006157775,0.001893297,0.000004091232,0.0005286455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00210123,"threshold_uncertainty_score":0.007029355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009512579921216952,"score_gpt":0.2341501885227917,"score_spread":0.2246376086015748,"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."}}