{"id":"W2807909645","doi":"10.1002/mrm.27352","title":"Neurovascular stent artifacts in 3D‐TOF and 3D‐PCMRI: Influence of stent design on flow measurement","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Stent; Neurovascular bundle; Lumen (anatomy); Streamlines, streaklines, and pathlines; Biomedical engineering; Radiology; Flow (mathematics); Materials science; Medicine; Anatomy; Surgery; Physics; Mathematics; Geometry; Mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008019347,0.0002023815,0.0004813055,0.0002147906,0.00003171598,0.000003335389,0.0001267242,0.00007801195,0.00006634084],"category_scores_gemma":[0.0004544782,0.0001575758,0.00002775876,0.0004503335,0.000413737,0.00004083418,0.00004648382,0.0002440372,0.000006842624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001083907,"about_ca_system_score_gemma":0.00005965175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001424432,"about_ca_topic_score_gemma":0.00005565373,"domain_scores_codex":[0.9978948,0.00007832977,0.0005969725,0.0004305151,0.000691315,0.0003080623],"domain_scores_gemma":[0.9988925,0.00009132157,0.0001081913,0.0005658785,0.0002181249,0.0001239254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001095494,0.0009477683,0.0283648,0.0003282645,0.000009835669,0.0001957781,0.001359389,0.005631989,0.06842922,0.0003916916,0.00123786,0.8920079],"study_design_scores_gemma":[0.005453283,0.008396753,0.9145649,0.004238665,0.00007897384,0.00005390721,0.0001449229,0.02058885,0.0106025,0.000733178,0.03483727,0.0003068155],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704111,0.008502504,0.01487935,0.003026445,0.00006139018,0.002231051,0.000002668426,0.00005630122,0.000829145],"genre_scores_gemma":[0.9569187,0.002892879,0.03873088,0.000979582,0.00009856135,0.0002276472,0.00000230808,0.00002675959,0.0001226507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8917011,"threshold_uncertainty_score":0.6425753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04853751963765052,"score_gpt":0.3003842172036389,"score_spread":0.2518466975659884,"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."}}