{"id":"W4387431658","doi":"10.1016/j.jstrokecerebrovasdis.2023.107374","title":"Prevalence of high-risk aortic arch atherosclerosis features on computed tomography angiography in embolic stroke of undetermined source","year":2023,"lang":"en","type":"article","venue":"Journal of Stroke and Cerebrovascular Diseases","topic":"Aortic Thrombus and Embolism","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Aortic arch; Embolic stroke; Stroke (engine); Radiology; Angiography; Computed tomography angiography; Cardiology; Computed tomography; Internal medicine; Aorta; Ischemic stroke; Ischemia","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004713718,0.0002570866,0.0003667753,0.001995746,0.0005386645,0.000891616,0.0004061839,0.0007893295,0.003739038],"category_scores_gemma":[0.003250017,0.0003419899,0.0004094595,0.001185103,0.0003580642,0.0006611128,0.0003993728,0.0004936492,0.0004051563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001663697,"about_ca_system_score_gemma":0.0002497916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002686222,"about_ca_topic_score_gemma":0.003417469,"domain_scores_codex":[0.9995412,0.0000941339,0.00007777072,0.00008392339,0.000100265,0.0001027905],"domain_scores_gemma":[0.998395,0.0005012177,0.0005809948,0.0001034295,0.0001653908,0.0002537931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007539291,0.00003057056,0.9987214,0.0000051453,0.00002066209,0.0002155755,0.00005827812,0.000008115238,0.0002249923,0.00001626262,0.00003135237,0.0005922325],"study_design_scores_gemma":[0.000002589826,0.00003966975,0.998412,0.00000434624,0.00002127386,0.001102687,0.0002045713,0.0001013227,0.00003858968,0.00002646197,0.00004303007,0.000003282179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989727,0.0001538796,0.00005657446,0.00002540127,0.000004614917,0.00000338374,0.0001153125,0.000002531553,0.0006657175],"genre_scores_gemma":[0.9996836,0.0000780811,0.00004021571,0.000009276202,0.00001340564,0.000001720984,0.00009386447,0.000001177247,0.00007879908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003739038,"threshold_uncertainty_score":0.01250827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008558703020788896,"score_gpt":0.2345194390256534,"score_spread":0.2259607360048645,"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."}}