{"id":"W3001769279","doi":"10.1103/physrevx.10.011015","title":"Nonlinear Dynamics of Human Aortas for Material Characterization","year":2020,"lang":"en","type":"article","venue":"Physical Review X","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Pulsatile flow; Thoracic aorta; Viscoelasticity; Descending aorta; Aorta; Biomedical engineering; Stiffness; Materials science; Nonlinear system; Mechanics; Physics; Computer science; Medicine; Cardiology; Composite material","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":[0.0002954243,0.0002930103,0.0001844962,0.0003420219,0.0001709399,0.0002739284,0.0001573065,0.0003073748,0.002406633],"category_scores_gemma":[0.0003849005,0.0001217355,0.0002262132,0.0002755882,0.0001946952,0.0002445334,0.000250182,0.0002601483,0.0005355265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000974633,"about_ca_system_score_gemma":0.0001970213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004276431,"about_ca_topic_score_gemma":0.0005547038,"domain_scores_codex":[0.9999373,0.00001405432,0.000003789002,0.00001581083,0.00002421256,0.000004822464],"domain_scores_gemma":[0.9998933,0.00005074427,0.00001475034,0.00001970405,0.00001705517,0.000004402098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009490865,0.0000755867,0.0035189,0.0002480029,0.00001817322,0.0001774952,0.0001694769,0.03130431,0.9131195,0.001999897,0.0004957296,0.04877801],"study_design_scores_gemma":[0.00002879375,0.000863283,0.06662192,0.0001658107,0.00008343261,0.001837341,0.0004011625,0.5160853,0.3754458,0.005335757,0.03303955,0.00009179688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6412798,0.004733835,0.3436358,0.0003289339,0.000122193,0.0001100877,0.001020067,0.0003366814,0.008432679],"genre_scores_gemma":[0.91829,0.004375181,0.06974027,0.00006884734,0.00004379197,0.0001617025,0.0005781777,0.00004687268,0.006695122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002406633,"threshold_uncertainty_score":0.008050978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259625881415544,"score_gpt":0.2777321834218604,"score_spread":0.255135924607705,"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."}}