{"id":"W4398784020","doi":"10.3390/app14114511","title":"Progressive Damage Simulation of Wood Veneer Laminates and Their Uncertainty Using Finite Element Analysis Informed by Genetic Algorithms","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Structural Analysis of Composite Materials","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"German Academic Exchange Service London","keywords":"Veneer; Finite element method; Computer science; Structural engineering; Algorithm; Materials science; Composite material; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005781716,0.0004545758,0.000422884,0.0007035361,0.0003281072,0.0005524155,0.0005539955,0.001068468,0.0008524481],"category_scores_gemma":[0.001533336,0.0003472584,0.0004991124,0.0003952026,0.0007024421,0.0003843395,0.0004085748,0.000578955,0.0001004571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008005369,"about_ca_system_score_gemma":0.0007628633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0102894,"about_ca_topic_score_gemma":0.008150002,"domain_scores_codex":[0.9998583,0.00005492802,0.000005979619,0.00001839148,0.00004124875,0.0000212025],"domain_scores_gemma":[0.9991338,0.0006483307,0.00007272568,0.00004347202,0.00007978598,0.00002182798],"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":[0.000004920985,0.000004506259,0.0001569412,0.000002493306,0.000002004802,0.000006435496,0.000007742829,0.9987308,0.000356585,0.0002185839,0.000007753833,0.0005011582],"study_design_scores_gemma":[8.81919e-7,0.000002598485,0.0000546193,8.531466e-7,6.041367e-7,0.000001242039,0.000002865102,0.9996209,0.0001487103,0.0001451379,0.00002055323,0.000001011278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7249355,0.0001858993,0.2687008,0.0001717255,0.0000214885,0.00006903384,0.0001418773,0.0003214638,0.005452216],"genre_scores_gemma":[0.970695,0.00005466822,0.02824425,0.0000198135,0.00000305414,0.00006109275,0.00006430344,0.00002966121,0.0008281934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0102894,"threshold_uncertainty_score":0.020459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225144716542659,"score_gpt":0.2631245609141753,"score_spread":0.2508731137487487,"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."}}