{"id":"W2604241566","doi":"10.1161/strokeaha.116.015636","title":"Computed Tomographic Perfusion Selection and Clinical Outcomes After Endovascular Therapy in Large Vessel Occlusion Stroke","year":2017,"lang":"en","type":"article","venue":"Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Thrombolysis; Modified Rankin Scale; Stroke (engine); Confidence interval; Perfusion scanning; Odds ratio; Internal medicine; Cerebral infarction; Perfusion; Cardiology; Myocardial infarction; Ischemia; 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":[0.0005652105,0.0001213731,0.0002000476,0.0008593508,0.0001435112,0.0004664933,0.0002106977,0.0002125517,0.0006705301],"category_scores_gemma":[0.00474606,0.00006973571,0.0002467002,0.001052776,0.0002757091,0.0002622451,0.0001852266,0.0002419148,0.00008092017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003290915,"about_ca_system_score_gemma":0.0003094377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00249836,"about_ca_topic_score_gemma":0.003260372,"domain_scores_codex":[0.9996424,0.0001079071,0.00006654862,0.00006022451,0.00007970785,0.00004321358],"domain_scores_gemma":[0.9965564,0.0007250211,0.0021863,0.00006744463,0.0002865488,0.0001783718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001208157,0.00001088022,0.9964091,0.00002552531,0.00004667252,0.00007626884,0.00001634974,0.00003286378,0.00008985817,0.00001101197,0.0001619551,0.002998612],"study_design_scores_gemma":[0.000006727545,0.00003866516,0.9989054,0.00002199483,0.00004825845,0.0005781338,0.00005563463,0.00009546193,0.00008174112,0.00002297035,0.0001431522,0.000001934521],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965363,0.002336534,0.00008427074,0.0001960047,0.00001546795,0.000008300757,0.0002816463,0.000002948331,0.0005386444],"genre_scores_gemma":[0.9991597,0.0005503391,0.00005392617,0.00003239351,0.00002580262,0.000003691773,0.0001521292,7.832305e-7,0.00002118472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00249836,"threshold_uncertainty_score":0.00496769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01646249436006914,"score_gpt":0.3064823723756737,"score_spread":0.2900198780156046,"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."}}