{"id":"W1509818742","doi":"10.1161/str.45.suppl_1.189","title":"Abstract 189: STAR: CT and MR Perfusion Imaging and Good Outcomes in Endovascular Stroke Treatment","year":2014,"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; Perfusion; Perfusion scanning; Stroke (engine); Radiology; Nuclear medicine; Magnetic resonance imaging","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":[0.001402211,0.0004006254,0.0004801681,0.0006524209,0.0002361212,0.0005714564,0.0002801359,0.0004394471,0.005732562],"category_scores_gemma":[0.001607515,0.0001453464,0.0003600557,0.000443535,0.0004804555,0.0005073531,0.0003965122,0.0003515671,0.0007008457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002187656,"about_ca_system_score_gemma":0.000368081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000261149,"about_ca_topic_score_gemma":0.0003554337,"domain_scores_codex":[0.9996098,0.0001724644,0.00005811668,0.00005240525,0.00005973531,0.00004755026],"domain_scores_gemma":[0.9990558,0.0001989664,0.0003615089,0.00004801537,0.00009061905,0.0002450806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01170873,0.0005495371,0.972099,0.0001057895,0.0002454666,0.0001715753,0.00003970136,0.0003187718,0.001321255,0.0001012456,0.001658592,0.01168022],"study_design_scores_gemma":[0.0009686006,0.003719474,0.990947,0.00004020262,0.0002120157,0.00115511,0.00006121604,0.001124139,0.0007066845,0.0002195859,0.0008346412,0.00001151989],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972573,0.0003595623,0.0002252117,0.0001993732,0.00002389955,0.00007574507,0.0004840399,0.000009926508,0.001364999],"genre_scores_gemma":[0.9978555,0.0001271856,0.0003367653,0.00007819791,0.0001047764,0.00006826166,0.001057429,0.000004561442,0.0003673547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005732562,"threshold_uncertainty_score":0.01917732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009229168537153137,"score_gpt":0.2481291351579324,"score_spread":0.2388999666207793,"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."}}