{"id":"W2312580428","doi":"10.1139/tcsme-2011-0020","title":"ADAPTIVE FINITE ELEMENT METHOD TO DETERMINE K<sub>I</sub> AND K<sub>II</sub> OF CRACK PLATE WITH DIFFERENT E<sub>INCLUSION</sub>/E<sub>PLATE</sub> RATIO","year":2011,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Commission on Higher Education","keywords":"Finite element method; Enhanced Data Rates for GSM Evolution; Stress intensity factor; Materials science; Inverse; Reflection (computer programming); Stress (linguistics); Fracture mechanics; Mathematical analysis; Geometry; Mathematics; Structural engineering; Composite material; Computer science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003325383,0.0004072333,0.0003060668,0.0003123167,0.0002843715,0.0002287087,0.0009062687,0.0006971326,0.00330685],"category_scores_gemma":[0.0008396031,0.0002503061,0.0003315899,0.0003148964,0.0003094288,0.0003643566,0.0003434421,0.000691084,0.0005667323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002372443,"about_ca_system_score_gemma":0.0007261764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002320454,"about_ca_topic_score_gemma":0.003740017,"domain_scores_codex":[0.9998711,0.00002759888,0.00000642945,0.00002353523,0.00006296636,0.000008315655],"domain_scores_gemma":[0.9996736,0.0001494924,0.00002308111,0.00002781876,0.0001136062,0.0000124246],"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":[0.0001596394,0.0001458535,0.002275284,0.0002206439,0.00008375831,0.000109907,0.0003259484,0.5951738,0.1094396,0.01470062,0.002059457,0.2753054],"study_design_scores_gemma":[0.00001057424,0.00002921116,0.0002317252,0.000007028794,0.000006887083,0.00004340169,0.00001677457,0.9912688,0.005536471,0.0007011408,0.002140317,0.000007756548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01003433,0.00003456775,0.9881192,0.00003813591,0.00001661259,0.00003378293,0.00002718986,0.0002339189,0.001462267],"genre_scores_gemma":[0.1604175,0.00009206296,0.8344862,0.00005489226,0.000009828256,0.0002991548,0.0001159827,0.00008462283,0.00443976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00330685,"threshold_uncertainty_score":0.01106244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01229768464500998,"score_gpt":0.1907035423180422,"score_spread":0.1784058576730322,"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."}}