{"id":"W2914428136","doi":"10.1161/str.50.suppl_1.116","title":"Abstract 116: MR PREDICTS@24H -- Multivariable Outcome Prediction After Endovascular Treatment for Acute Ischemic Stroke: Development and Validation of a Prognostic Model in Data From Seven RCTs","year":2019,"lang":"en","type":"article","venue":"Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Logistic regression; Modified Rankin Scale; Stroke (engine); Revascularization; Randomized controlled trial; Ordinal regression; Internal medicine; Cardiology; Ischemic stroke; Statistics; Ischemia; Myocardial infarction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1329647,0.001234181,0.002286791,0.001490841,0.0003317787,0.001792542,0.001604809,0.0008717298,0.002679673],"category_scores_gemma":[0.142451,0.0004871802,0.006636701,0.002049209,0.0007205389,0.001107603,0.001732951,0.001349036,0.0004924017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007654637,"about_ca_system_score_gemma":0.002161083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00223897,"about_ca_topic_score_gemma":0.001880719,"domain_scores_codex":[0.9051368,0.08407065,0.004980657,0.002662261,0.002588368,0.0005612952],"domain_scores_gemma":[0.7607274,0.2098771,0.01444107,0.008637426,0.00567611,0.0006409446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.02848572,0.001089529,0.7325625,0.008113139,0.07434481,0.0004364082,0.0005541073,0.0704288,0.001157736,0.001992325,0.006762919,0.074072],"study_design_scores_gemma":[0.01646011,0.01484166,0.4378596,0.002727447,0.07463424,0.0008450513,0.0004423184,0.4277754,0.003009027,0.00788508,0.01317132,0.0003487481],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9179284,0.007336068,0.04984252,0.001806195,0.0002358848,0.003280159,0.01693251,0.0003851239,0.002253158],"genre_scores_gemma":[0.9786362,0.0004360807,0.0138101,0.0001506371,0.00004721519,0.001568067,0.005112194,0.00003819237,0.0002012089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1329647,"threshold_uncertainty_score":0.7031931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03537280123975356,"score_gpt":0.2874401145047596,"score_spread":0.2520673132650061,"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."}}