{"id":"W2164125464","doi":"10.1007/bf03181639","title":"A realistic coronary artery phantom for particle image velocimetry","year":2004,"lang":"en","type":"article","venue":"Journal of Visualization","topic":"Coronary Interventions and Diagnostics","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Montreal Heart Institute","funders":"Institut de Cardiologie de Montréal; Polytechnique Montréal; McGill University","keywords":"Imaging phantom; Particle image velocimetry; Particle tracking velocimetry; Velocimetry; Materials science; Biomedical engineering; Particle (ecology); Artery; Physics; Medicine; Mechanics; Optics; Cardiology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002092298,0.00006881056,0.000171365,0.00009406955,0.00004801947,0.00002097488,0.00003992485,0.0000397759,0.00008277025],"category_scores_gemma":[0.0004868228,0.00005941164,0.0001434701,0.0001444524,0.00002754174,0.0001646689,0.000009196453,0.00005553494,0.000008465275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009320521,"about_ca_system_score_gemma":0.0001174285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000391127,"about_ca_topic_score_gemma":0.000003099125,"domain_scores_codex":[0.9992026,0.00001722774,0.0004226376,0.00006858534,0.0001779923,0.0001109635],"domain_scores_gemma":[0.999104,0.00008514475,0.0002205229,0.00008189231,0.0004142985,0.00009415039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01642308,0.02965591,0.16931,0.003672634,0.002848883,0.006069615,0.00698349,0.00464977,0.3679665,0.140048,0.0708064,0.1815657],"study_design_scores_gemma":[0.06172807,0.03314746,0.6551313,0.00573074,0.004090444,0.01695926,0.002800739,0.02295553,0.1431215,0.03674901,0.01649484,0.001091104],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6888893,0.0004189502,0.3095503,0.0005876413,0.0002544117,0.0001816438,0.00001145535,0.00001451836,0.00009172004],"genre_scores_gemma":[0.994877,0.0001170648,0.004315319,0.0002694446,0.0002591333,0.000004298874,0.00003186014,0.00001533248,0.0001105005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4858212,"threshold_uncertainty_score":0.2422736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02933576460370691,"score_gpt":0.3707608841706466,"score_spread":0.3414251195669397,"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."}}