{"id":"W4396998546","doi":"10.1016/j.ijengsci.2024.104092","title":"A pseudoelastic response of hyperelastic composites reinforced with nonlinear elastic fibrous materials: Continuum modeling and analysis","year":2024,"lang":"en","type":"article","venue":"International Journal of Engineering Science","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Canada Research Chairs; University of Toronto","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Hyperelastic material; Materials science; Composite material; Nonlinear system; Pseudoelasticity; Nonlinear elasticity; Structural engineering; Finite element method; Physics; Microstructure; Engineering","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":[0.0002081991,0.0004375602,0.000270676,0.0004206803,0.0002457199,0.0005207058,0.0006251435,0.001190087,0.0008643327],"category_scores_gemma":[0.0003731464,0.0002483397,0.0005081817,0.000252611,0.0006344501,0.0006051554,0.0004396084,0.0004440723,0.0002726065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002721199,"about_ca_system_score_gemma":0.0004541459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001393015,"about_ca_topic_score_gemma":0.001162971,"domain_scores_codex":[0.9999042,0.00002599294,0.000004362351,0.00001844229,0.00003561122,0.00001129347],"domain_scores_gemma":[0.9998957,0.00003616374,0.00002409031,0.00001744398,0.00001664639,0.000009879312],"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":[0.00002528071,0.00006711957,0.0007119521,0.00005964826,0.00001226832,0.0002170352,0.00008564623,0.9446332,0.03557935,0.01273172,0.0001297342,0.005747093],"study_design_scores_gemma":[0.00000119614,0.00001301295,0.0001969554,0.000003384155,0.000001428305,0.00002782271,0.000006931634,0.9976382,0.001010312,0.0008721434,0.0002249368,0.000003613672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2539833,0.001043381,0.7303493,0.0003867057,0.0000744032,0.00008459587,0.0001272314,0.0001967889,0.01375427],"genre_scores_gemma":[0.9530196,0.0007989173,0.03693836,0.00008176178,0.0000218363,0.0001199767,0.00006386059,0.0000430332,0.008912627],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001393015,"threshold_uncertainty_score":0.002891481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006191051069532339,"score_gpt":0.2198232495656875,"score_spread":0.2136321984961552,"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."}}