{"id":"W4392131313","doi":"10.1007/s00234-024-03309-y","title":"Phase-contrast magnetic resonance imaging of intracranial and extracranial blood flow in carotid near-occlusion","year":2024,"lang":"en","type":"article","venue":"Neuroradiology","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"STROKE-Riksförbundet; Västra Götalandsregionen; Hjärt-Lungfonden; Svenska Läkaresällskapet; Knut och Alice Wallenbergs Stiftelse; Jeanssons Stiftelser","keywords":"Medicine; Stenosis; Internal carotid artery; Asymptomatic; Neuroradiology; Blood flow; Occlusion; Magnetic resonance imaging; Cerebral blood flow; Collateral circulation; Radiology; Magnetic resonance angiography; Middle cerebral artery; Cardiology; Internal medicine; Neurology; Ischemia","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":[0.0004155241,0.0002348446,0.0002987361,0.0008244507,0.0001109344,0.0002251564,0.00009551305,0.0002138871,0.000871132],"category_scores_gemma":[0.001644294,0.000133388,0.0001316796,0.0003411107,0.0002460596,0.0002963287,0.0002169996,0.0001398319,0.0001503351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001336679,"about_ca_system_score_gemma":0.0001773402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003611809,"about_ca_topic_score_gemma":0.0005797559,"domain_scores_codex":[0.9998777,0.00002831706,0.00001802044,0.00002451394,0.00002522492,0.00002614351],"domain_scores_gemma":[0.9995136,0.000149843,0.0001991758,0.00002030836,0.0000366608,0.00008025581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001206947,0.00009527519,0.9839571,0.00004609734,0.00003689106,0.001040521,0.000108893,0.0001523655,0.00557373,0.00003113248,0.00005618208,0.007695011],"study_design_scores_gemma":[0.00004114688,0.0006355065,0.9933083,0.000009156881,0.00003561469,0.004704101,0.0000808423,0.0003644976,0.0006685225,0.00004136379,0.0001057037,0.000005138107],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995806,0.000145785,0.0000865323,0.000004147142,0.000001205012,0.000004819162,0.00001449194,0.000001521529,0.0001609518],"genre_scores_gemma":[0.999738,0.00006054286,0.0000992131,0.000006512976,0.000007133539,0.000004755289,0.00004616496,6.334456e-7,0.00003691559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000871132,"threshold_uncertainty_score":0.00291419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005747161928598746,"score_gpt":0.2439855492965134,"score_spread":0.2382383873679147,"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."}}