{"id":"W2892184016","doi":"10.1161/strokeaha.118.022114","title":"Endovascular Thrombectomy for Mild Strokes: How Low Should We Go?","year":2018,"lang":"en","type":"article","venue":"Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; National Institutes of Health; Stryker","keywords":"Medicine; Stroke (engine); Intracerebral hemorrhage; Thrombus; Occlusion; Odds ratio; Propensity score matching; Logistic regression; Computed tomographic; Cohort; Retrospective cohort study; Cerebral infarction; Thrombolysis; Surgery; Internal medicine; Myocardial infarction; Computed tomography; Glasgow Coma Scale; 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":[0.000255686,0.0003424802,0.0005326349,0.0001703367,0.0001320107,0.00005272165,0.0002877627,0.0001701209,0.0004611141],"category_scores_gemma":[0.000168908,0.0002939362,0.0004295742,0.0001737651,0.0002427829,0.0001224347,0.000148626,0.0002447681,0.000220577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001491592,"about_ca_system_score_gemma":0.00007903168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001770168,"about_ca_topic_score_gemma":0.00001515305,"domain_scores_codex":[0.9978446,0.00002494694,0.0002709818,0.0006041442,0.0005650041,0.000690346],"domain_scores_gemma":[0.998456,0.00008935264,0.0001118588,0.0009065056,0.0002159116,0.0002203836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004716027,0.0003028355,0.008147462,0.0006089005,0.00177055,0.00005503575,0.0005099764,0.000001643872,0.08261554,0.0008115612,0.8899543,0.01475054],"study_design_scores_gemma":[0.004940952,0.0007966614,0.002187216,0.0001758275,0.0005622508,0.00002685023,0.0006954388,0.0004326837,0.1301448,0.00004010126,0.859665,0.0003322096],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6507033,0.003503455,0.08899444,0.0406169,0.003518376,0.007600721,0.0006829862,0.001203673,0.2031762],"genre_scores_gemma":[0.9168466,0.0001685381,0.02399587,0.001929536,0.002791322,0.0002844346,0.0000996036,0.0001166139,0.0537675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2661433,"threshold_uncertainty_score":0.9999513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03742477297398515,"score_gpt":0.2945270355938568,"score_spread":0.2571022626198716,"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."}}