{"id":"W1009567930","doi":"10.1016/j.engfracmech.2015.07.044","title":"Adaptive insertion of cohesive elements for simulation of delamination in laminated composite materials","year":2015,"lang":"en","type":"article","venue":"Engineering Fracture Mechanics","topic":"Mechanical Behavior of Composites","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Delamination (geology); Composite number; Materials science; Finite element method; Structural engineering; A priori and a posteriori; Transient (computer programming); Mode (computer interface); Benchmark (surveying); Cohesive zone model; Composite laminates; Composite material; Computer science; Engineering; Geology","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":[0.0002994082,0.0001656438,0.0003089807,0.0002038451,0.000007457645,0.000007075924,0.0001160912,0.0001552641,0.000008046222],"category_scores_gemma":[0.0001294875,0.0001827648,0.00004012922,0.0001999649,0.000003596247,0.0001414086,0.00001896182,0.00009673098,0.000001192176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001308219,"about_ca_system_score_gemma":0.00001159218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000668551,"about_ca_topic_score_gemma":0.000002399031,"domain_scores_codex":[0.9989831,0.00002205943,0.0005007481,0.0001234611,0.0002053348,0.0001652548],"domain_scores_gemma":[0.9993412,0.000142975,0.0001231013,0.000143002,0.0001990613,0.0000506848],"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":[0.00004038369,0.00002369064,0.00001328612,0.00007660734,0.00001451311,5.627609e-7,0.0001196187,0.6174291,0.3812703,0.0006709645,0.00000542971,0.0003354568],"study_design_scores_gemma":[0.0004159058,0.0001042413,0.0002986386,0.00007180148,0.00001947006,3.631968e-7,0.00001492648,0.5355259,0.4630729,0.0003422815,0.00004166467,0.00009195114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4683088,0.00005354698,0.5309981,0.000005328506,0.0002052533,0.00033135,0.00002799046,0.00006571895,0.000003856468],"genre_scores_gemma":[0.9831352,0.000003935359,0.01665711,0.000004981625,0.0000238481,0.00003708392,0.00009499139,0.00004029891,0.000002505617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5148264,"threshold_uncertainty_score":0.745293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0184096317019697,"score_gpt":0.2464836727191226,"score_spread":0.2280740410171529,"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."}}