{"id":"W2551395262","doi":"10.1121/1.4969394","title":"Robust and high-frame-rate visualization of arterial pulse wave propagation dynamics","year":2016,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Cardiovascular Health and Disease Prevention","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Frame rate; Visualization; Temporal resolution; Wave propagation; Acoustics; Millisecond; Computer vision; Artificial intelligence; Algorithm; Physics; Optics","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":[0.0009464528,0.0003827839,0.0003808747,0.0009613073,0.0001920421,0.001063984,0.0003794866,0.0005264194,0.00258412],"category_scores_gemma":[0.002319465,0.0002681776,0.0002330612,0.000470802,0.0003403896,0.0008553173,0.000558992,0.0007962498,0.0006343781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001981672,"about_ca_system_score_gemma":0.0003702653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007018546,"about_ca_topic_score_gemma":0.0009470635,"domain_scores_codex":[0.9997433,0.00006996245,0.00001515545,0.00004395542,0.0001052846,0.00002243831],"domain_scores_gemma":[0.9993526,0.0002969439,0.00006833546,0.00008828798,0.0001581238,0.00003571758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002152102,0.0000690704,0.001994621,0.0001679606,0.0000421662,0.0002196485,0.0001910452,0.02113769,0.7348764,0.005461251,0.003518273,0.2321067],"study_design_scores_gemma":[0.00005132256,0.0002532046,0.01931274,0.00007594139,0.00006755946,0.001535328,0.00014954,0.5711807,0.3850607,0.008715854,0.01345502,0.0001420455],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03739775,0.0003051094,0.9585416,0.0002285656,0.00004194204,0.00005423165,0.0002643575,0.001583454,0.001582857],"genre_scores_gemma":[0.2041966,0.0006535639,0.7926794,0.00007848561,0.00008090908,0.0001022493,0.0003090575,0.0003553392,0.001544431],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00258412,"threshold_uncertainty_score":0.00864476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01294093758199644,"score_gpt":0.259583239364115,"score_spread":0.2466423017821186,"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."}}