{"id":"W2163483046","doi":"10.1115/1.4000371","title":"Improved Prediction Method for Estimating Notch Elastic-Plastic Strain","year":2009,"lang":"en","type":"article","venue":"Journal of Pressure Vessel Technology","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Structural engineering; Finite element method; Nonlinear system; Materials science; Strain (injury); Stress (linguistics); Linear elasticity; Stress relaxation; Component (thermodynamics); Stress–strain curve; Composite material; Physics; Creep; Engineering; Thermodynamics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000344351,0.0001614752,0.0003239291,0.000350169,0.00005226849,0.00002180492,0.0002518225,0.0003360792,0.000009577384],"category_scores_gemma":[0.0006309152,0.000143164,0.00008459806,0.0002267659,0.00001602698,0.0001641218,0.00001201822,0.0005256118,9.006302e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002598429,"about_ca_system_score_gemma":0.00002783738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.204835e-7,"about_ca_topic_score_gemma":5.518658e-7,"domain_scores_codex":[0.9990205,0.00001603938,0.0004718962,0.0001161587,0.0001205782,0.000254847],"domain_scores_gemma":[0.9991948,0.0002101682,0.0002115623,0.0001578617,0.0001700317,0.00005555717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005170905,0.00006165655,0.0000125361,0.0001770655,0.0002434534,0.00001366596,0.0001283464,0.1737367,0.6616187,0.002330828,0.002551119,0.1590742],"study_design_scores_gemma":[0.0006991186,0.0007239348,0.00007217977,0.00009805585,0.0002344679,0.0001704642,0.00005791762,0.9397064,0.03892162,0.01149931,0.007677122,0.0001394095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00224386,0.0006824693,0.9947013,0.000483907,0.001409607,0.0001612173,0.00003357399,0.0002362795,0.00004783157],"genre_scores_gemma":[0.5470772,0.0000163217,0.45253,0.00002435541,0.0003115047,0.00000556253,0.000002549031,0.00002124431,0.00001128662],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7659697,"threshold_uncertainty_score":0.5838059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008299695547321547,"score_gpt":0.2527008372585968,"score_spread":0.2444011417112752,"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."}}