{"id":"W2912163064","doi":"10.1161/str.50.suppl_1.wp9","title":"Abstract WP9: Improving Selection of Patients for Endovascular Treatment of Acute Ischemic Stroke:External Validation of a Clinical Decision Tool in Data from the Hermes Collaboration","year":2019,"lang":"en","type":"article","venue":"Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Brain Institute","funders":"","keywords":"Medicine; Confidence interval; Logistic regression; Modified Rankin Scale; Randomized controlled trial; Stroke (engine); Statistic; Clinical trial; Calibration; Statistics; Internal medicine; Ischemic stroke","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2031226,0.001963401,0.002013151,0.002331973,0.000701412,0.003813039,0.002656021,0.001530456,0.004633341],"category_scores_gemma":[0.3947298,0.000593261,0.003480613,0.003630387,0.001342063,0.002177694,0.004961864,0.00197966,0.001544223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001246096,"about_ca_system_score_gemma":0.003714084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002973887,"about_ca_topic_score_gemma":0.001594084,"domain_scores_codex":[0.7815621,0.1752243,0.01475079,0.01028547,0.01686419,0.001313071],"domain_scores_gemma":[0.535733,0.3401897,0.05012026,0.0465957,0.0242248,0.003136548],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03899409,0.001672597,0.736451,0.002936604,0.01962455,0.0003893663,0.001554197,0.03919166,0.0007218588,0.005342742,0.04695969,0.1061618],"study_design_scores_gemma":[0.01879077,0.007834492,0.6940573,0.002006456,0.007274583,0.001003225,0.0007005585,0.2006385,0.004808277,0.0143477,0.04796828,0.0005698761],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.793851,0.002153294,0.08547168,0.003716571,0.0005805428,0.006530469,0.09331675,0.001352466,0.01302712],"genre_scores_gemma":[0.9355662,0.0002241276,0.02530604,0.0005085069,0.000194494,0.005004099,0.03192814,0.0002861705,0.0009822304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7968774,"threshold_uncertainty_score":0.9826918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02847640864852135,"score_gpt":0.3350058723306598,"score_spread":0.3065294636821385,"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."}}