{"id":"W2038508252","doi":"10.1159/000362591","title":"Posttreatment Variables Improve Outcome Prediction after Intra-Arterial Therapy for Acute Ischemic Stroke","year":2014,"lang":"en","type":"article","venue":"Cerebrovascular Diseases","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Medicine; Cohort; Internal medicine; Logistic regression; Stroke (engine); Solitaire Cryptographic Algorithm; Confidence interval; Prospective cohort study; Cohort study; Cardiology; Surgery; Modified Rankin Scale; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001505089,0.0003951169,0.0005712634,0.000116786,0.00009454707,0.00006459546,0.0001663396,0.0001365588,0.0003556457],"category_scores_gemma":[0.00009613429,0.0003174696,0.0006557048,0.00008968701,0.00008403112,0.0001510584,0.00008801017,0.0001050967,0.00004633533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001806251,"about_ca_system_score_gemma":0.00006721093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000156535,"about_ca_topic_score_gemma":6.907082e-7,"domain_scores_codex":[0.9979349,0.00004373037,0.0004441345,0.0006738163,0.0004216658,0.0004817811],"domain_scores_gemma":[0.9985122,0.00006655643,0.0001075201,0.0008944116,0.0001310741,0.00028821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0126389,0.00396056,0.4651431,0.001174634,0.02635778,0.00005822765,0.0004037972,0.00002633681,0.2362867,0.0002887822,0.143463,0.1101982],"study_design_scores_gemma":[0.05028984,0.003787198,0.2336646,0.000251328,0.01808107,0.00007450834,0.0002454289,0.002313931,0.09284411,0.0001769292,0.5968591,0.001411909],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9732389,0.001021714,0.01735505,0.0007081178,0.001165919,0.003136901,0.001243962,0.0003511831,0.001778204],"genre_scores_gemma":[0.9882162,0.0002886103,0.003491249,0.001467587,0.001534946,0.001689805,0.0009063798,0.0001063184,0.002298919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4533961,"threshold_uncertainty_score":0.9999278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007620085192628399,"score_gpt":0.2475667550777156,"score_spread":0.2399466698850872,"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."}}