{"id":"W3014417414","doi":"10.1177/1747493020915141","title":"CT perfusion core and ASPECT score prediction of outcomes in DEFUSE 3","year":2020,"lang":"en","type":"article","venue":"International Journal of Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Medicine; Modified Rankin Scale; Logistic regression; Infarction; Stroke (engine); Perfusion scanning; Core (optical fiber); Internal medicine; Clinical trial; Cardiology; Perfusion; Myocardial infarction; 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":[0.001654886,0.0003762896,0.000666079,0.0003836449,0.0001927478,0.0006860407,0.0003120278,0.0004052849,0.001094883],"category_scores_gemma":[0.002412537,0.0001173384,0.0005583964,0.0003647463,0.0003914269,0.0003299287,0.0004566346,0.0005715709,0.0001011498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002427359,"about_ca_system_score_gemma":0.0004283187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001150555,"about_ca_topic_score_gemma":0.002369545,"domain_scores_codex":[0.9996009,0.0001721099,0.00003185305,0.00005106172,0.00007723822,0.00006692505],"domain_scores_gemma":[0.9985914,0.0004420014,0.0004417119,0.00006972845,0.0001065774,0.0003485924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02735276,0.0004404565,0.9509168,0.0000569796,0.0005206296,0.00007378035,0.00003962173,0.0005167681,0.001226828,0.000090194,0.0004578047,0.01830734],"study_design_scores_gemma":[0.001940396,0.004602101,0.9887069,0.00003490986,0.0004033606,0.0003611131,0.00004402389,0.002487801,0.0004671409,0.0003987712,0.0005396084,0.00001383309],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985781,0.0006008095,0.0001520867,0.00008653071,0.00000682669,0.00002990587,0.0001362218,0.000003421478,0.000406176],"genre_scores_gemma":[0.9989882,0.0001566173,0.0002712045,0.00006280776,0.00003566662,0.0000264577,0.0003771022,0.000002011131,0.00007987309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001654886,"threshold_uncertainty_score":0.008751929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0337915204361043,"score_gpt":0.2861386212625934,"score_spread":0.2523471008264891,"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."}}