{"id":"W2341083644","doi":"10.1007/978-3-319-19387-8_423","title":"Investigation of flow and turbulence in carotid artery models of varying compliance using particle image velocimetry","year":2015,"lang":"en","type":"book-chapter","venue":"World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany","topic":"Cardiovascular Health and Disease Prevention","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Ontario Ministry of Research and Innovation","keywords":"Particle image velocimetry; Turbulence; Compliance (psychology); Particle tracking velocimetry; Mechanics; Velocimetry; Particle (ecology); Carotid arteries; Physics; Geology; Medicine; Cardiology; Psychology; Oceanography; Social psychology","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":[0.0003185922,0.0005071575,0.0005079458,0.0005891664,0.000374811,0.0007978475,0.0004703281,0.0008503076,0.000593468],"category_scores_gemma":[0.00085296,0.0003498123,0.0005930637,0.0004439476,0.0004348684,0.0004050413,0.0003388066,0.0005054554,0.0001206662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004392015,"about_ca_system_score_gemma":0.0008191745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005818787,"about_ca_topic_score_gemma":0.003921059,"domain_scores_codex":[0.9998876,0.0000227978,0.000008366215,0.00002460729,0.00003639057,0.00002026918],"domain_scores_gemma":[0.9995951,0.0002395175,0.00006113753,0.0000331075,0.00005214544,0.00001894911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003650333,0.0005604679,0.006650616,0.0001563866,0.00007788278,0.0003593555,0.0002506305,0.8010945,0.1657677,0.005210997,0.001122304,0.01838416],"study_design_scores_gemma":[0.0000169786,0.0001110406,0.002001033,0.000007559679,0.00002201087,0.00005102553,0.00002155585,0.9844421,0.01247633,0.0004310228,0.0003967044,0.00002259066],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9167482,0.0007036191,0.07745849,0.000258323,0.00007931674,0.00008274589,0.0006318543,0.0005443908,0.003492962],"genre_scores_gemma":[0.9788043,0.0005569115,0.01769003,0.00004207729,0.00001872397,0.00007385217,0.0003310514,0.00006575631,0.002417266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005818787,"threshold_uncertainty_score":0.01156986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04646211477000677,"score_gpt":0.2795422622614685,"score_spread":0.2330801474914617,"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."}}