{"id":"W2160298880","doi":"10.1161/01.str.0000196985.38701.0c","title":"Validation of Automatically Classified Magnetic Resonance Images for Carotid Plaque Compositional Analysis","year":2005,"lang":"en","type":"article","venue":"Stroke","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Medicine; Magnetic resonance imaging; Histopathology; Lesion; Radiology; Carotid endarterectomy; Contrast (vision); Nuclear medicine; Calcification; Pathology; Stenosis; Artificial intelligence","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":[0.01122991,0.0009464956,0.0007144289,0.002692854,0.0005130133,0.001138614,0.001183128,0.001534367,0.0009565832],"category_scores_gemma":[0.02699018,0.0003408832,0.0006151203,0.00059042,0.000611282,0.0007964434,0.0007236007,0.0005304954,0.001071091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004321929,"about_ca_system_score_gemma":0.0006232716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008753038,"about_ca_topic_score_gemma":0.001031988,"domain_scores_codex":[0.9944623,0.002846781,0.0004222723,0.0008759224,0.001195005,0.0001976781],"domain_scores_gemma":[0.979555,0.01038486,0.001980221,0.002207479,0.005604697,0.0002677743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005752613,0.001420693,0.357847,0.0007525348,0.001091334,0.000441514,0.0006042123,0.03632421,0.2363711,0.00059625,0.002247798,0.3565508],"study_design_scores_gemma":[0.0003930426,0.00173054,0.2639723,0.0001890521,0.0005529137,0.001778162,0.0002030434,0.5656105,0.1621194,0.001037944,0.002269453,0.0001436762],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8514595,0.000639638,0.1436136,0.000115603,0.00009165752,0.0003718731,0.0006876143,0.001737308,0.001283238],"genre_scores_gemma":[0.9065334,0.0001234264,0.09099811,0.00009818914,0.0000613001,0.0002404037,0.001535444,0.0001361885,0.0002736561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01122991,"threshold_uncertainty_score":0.05939013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009777639376839353,"score_gpt":0.2588213230931276,"score_spread":0.2490436837162882,"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."}}