{"id":"W4321763991","doi":"10.1016/j.tafmec.2023.103818","title":"3D fracture study of cracked functionally graded biological materials by XIGA approach using Bézier extraction of NURBS","year":2023,"lang":"en","type":"article","venue":"Theoretical and Applied Fracture Mechanics","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Department of Mechanical Engineering, University of Alberta; Shiv Nadar University","keywords":"Discretization; Isogeometric analysis; Basis function; Functionally graded material; Bézier curve; Material properties; Materials science; Structural engineering; Computer science; Mathematics; Geometry; Engineering; Finite element method; Composite material; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003719462,0.0002805365,0.0006097783,0.000104798,0.00006243514,0.00001495115,0.0001514414,0.0003222807,0.0002054166],"category_scores_gemma":[0.00004583475,0.0002032223,0.00006247003,0.0004357163,0.0001319467,0.00005566997,0.00006695432,0.0003321448,0.000003281981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002425824,"about_ca_system_score_gemma":0.00000474638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003195665,"about_ca_topic_score_gemma":1.340345e-7,"domain_scores_codex":[0.9985452,0.00007461382,0.0004888238,0.0003285919,0.0003039864,0.0002588432],"domain_scores_gemma":[0.9992882,0.0001999505,0.0001392798,0.0002375807,0.00004907512,0.00008590094],"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":[0.0001789008,0.0003757736,0.000007864393,0.00007876152,0.0001452311,0.000001711017,0.0002130374,0.01060329,0.9389054,0.04801175,0.000162926,0.001315416],"study_design_scores_gemma":[0.0007039576,0.0003299387,0.0001637162,0.00002371551,0.0002489031,0.000008206544,0.0008919354,0.03657087,0.7209404,0.2391613,0.0004407651,0.0005163265],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5369948,0.00004047943,0.4621312,0.00002376847,0.00004184805,0.0003373071,0.00002475818,0.0002792151,0.0001266195],"genre_scores_gemma":[0.9940105,0.00006551099,0.005600763,0.0000797543,0.00006168835,0.00004030328,0.00009684778,0.00004060881,0.000004015402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4570157,"threshold_uncertainty_score":0.8287166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01181043047836519,"score_gpt":0.2453193763857594,"score_spread":0.2335089459073942,"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."}}