{"id":"W3205785651","doi":"10.1161/strokeaha.120.032527","title":"External Validation of Risk Prediction Models to Improve Selection of Patients for Carotid Endarterectomy","year":2021,"lang":"en","type":"article","venue":"Stroke","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute","keywords":"Carotid endarterectomy; Stroke (engine); Selection (genetic algorithm); Endarterectomy; Predictive modelling; Risk assessment; Predictive value of tests; Predictive value","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":[0.1648701,0.00184596,0.002690878,0.007062294,0.0004826516,0.003564466,0.002751144,0.001640143,0.001385087],"category_scores_gemma":[0.3690116,0.0008007037,0.004785025,0.005494324,0.001220789,0.002361109,0.002509518,0.001888586,0.0003494722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00111831,"about_ca_system_score_gemma":0.002886777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002225715,"about_ca_topic_score_gemma":0.001895847,"domain_scores_codex":[0.9136519,0.06429021,0.009366921,0.006011684,0.006136753,0.0005424869],"domain_scores_gemma":[0.406048,0.525695,0.02832683,0.01935011,0.01963703,0.0009432095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002663553,0.0005199735,0.8561661,0.003423234,0.01569563,0.0002872421,0.0006948174,0.03188976,0.0004106652,0.001506743,0.003654863,0.08308735],"study_design_scores_gemma":[0.003593435,0.003789951,0.490647,0.008741491,0.0310088,0.001390235,0.0008793392,0.4326564,0.003534183,0.01316049,0.01022005,0.0003785856],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8415581,0.01983272,0.1174838,0.002322606,0.0005935938,0.00165507,0.007292717,0.00073815,0.008523214],"genre_scores_gemma":[0.9779441,0.001172946,0.01524294,0.0003196354,0.0001131665,0.0003849958,0.004652517,0.00005798139,0.0001117384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1648701,"threshold_uncertainty_score":0.8719267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009830127714397802,"score_gpt":0.237791045107107,"score_spread":0.2279609173927092,"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."}}