{"id":"W2783373744","doi":"10.48550/arxiv.1801.04027","title":"A New Continuum-Based Thick Shell Finite Element for Soft Biological Tissues in Dynamics: Part 2 - Anisotropic Hyperelasticity and Incompressibility Aspects","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hyperelastic material; Finite element method; Constitutive equation; Lagrange multiplier; Nonlinear system; Compressibility; Shell (structure); Anisotropy; Classical mechanics; Mechanics; Materials science; Physics; Mathematics; Structural engineering; Engineering; Composite material; Mathematical optimization","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001745357,0.0003481362,0.0004901133,0.0001310585,0.00007725639,0.0000619544,0.0002991955,0.0004380715,0.00007704942],"category_scores_gemma":[0.0001088958,0.0003792226,0.00009342762,0.0001025685,0.0001172594,0.00008607447,0.0003579383,0.0003812029,0.00001239881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002441795,"about_ca_system_score_gemma":0.00008364268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002531374,"about_ca_topic_score_gemma":0.001678342,"domain_scores_codex":[0.9984911,0.00007431817,0.0003024585,0.0007007628,0.00004913577,0.0003822372],"domain_scores_gemma":[0.9990243,0.0003170079,0.00009213256,0.0003413465,0.00007258001,0.0001526607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002966597,0.0000960321,0.01089962,0.0006567955,0.00008772765,0.00004354626,0.0001097558,0.9813896,0.0003245548,0.005728848,0.0001255824,0.0002413257],"study_design_scores_gemma":[0.001154037,0.0001669512,0.001752817,0.0003121809,0.00007801651,4.849193e-7,0.00003156906,0.9647448,0.0005519852,0.03047395,0.0003061384,0.0004270379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5497132,0.00005696308,0.449068,0.00001002472,0.0003676026,0.0003653415,0.0001003796,0.0001571524,0.0001613841],"genre_scores_gemma":[0.9965915,0.0001075917,0.002917212,0.00002423482,0.000177596,0.000004213256,0.00008591379,0.00002760023,0.00006413362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4468783,"threshold_uncertainty_score":0.9998659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0556061049540358,"score_gpt":0.1922429180114504,"score_spread":0.1366368130574145,"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."}}