{"id":"W2887720980","doi":"10.1007/s10237-018-1060-5","title":"Nonlinear model of human descending thoracic aortic segments with residual stresses","year":2018,"lang":"en","type":"article","venue":"Biomechanics and Modeling in Mechanobiology","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Qatar National Research Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Qatar Foundation","keywords":"Materials science; Hyperelastic material; Nonlinear system; Residual stress; Mechanics; Shell (structure); Thoracic aorta; Structural engineering; Finite element method; Descending aorta; Aorta; Deformation (meteorology); Composite material; Physics; Engineering; Surgery","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":[0.000213588,0.0001881564,0.0002895907,0.0002467652,0.00007912481,0.00001678408,0.0001250742,0.0001783216,0.000005673481],"category_scores_gemma":[0.000009534824,0.000170419,0.00001722628,0.0001297783,0.00004341665,0.00007051138,0.00007648354,0.0001124766,0.000001378045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002779605,"about_ca_system_score_gemma":0.00001872946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003737782,"about_ca_topic_score_gemma":0.0000820082,"domain_scores_codex":[0.9989687,0.00001779316,0.0003404749,0.0002605337,0.00008103662,0.0003314809],"domain_scores_gemma":[0.9996789,0.00001532246,0.00004771102,0.0001344635,0.00006999796,0.00005367769],"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":[0.00004812907,0.00002774914,0.000007425522,0.0001264316,0.00002325851,0.000001115929,0.000182791,0.0596089,0.9371181,0.00203369,0.00000107851,0.0008213137],"study_design_scores_gemma":[0.0002097473,0.0002237648,1.277322e-7,0.0001389146,0.00001734105,0.000002909185,0.00007060273,0.7325425,0.2623957,0.004254589,7.341658e-7,0.0001430427],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7650983,0.00005654283,0.2344804,0.000004956216,0.0001252799,0.0001036684,0.00002398641,0.00006690915,0.00003994679],"genre_scores_gemma":[0.9804829,0.00013958,0.01922096,0.00001421835,0.00007311263,0.00001163834,0.00001666891,0.00003527736,0.000005639741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6747224,"threshold_uncertainty_score":0.6949486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04931241723947651,"score_gpt":0.2783476794685154,"score_spread":0.2290352622290388,"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."}}