{"id":"W2765406999","doi":"10.1063/1.5008097","title":"Finite element simulation of non-isothermal warm forming of high-strength aluminum alloy sheet","year":2017,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Metal Forming Simulation Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Honda Development and Manufacturing of America","keywords":"Materials science; Blank; Isothermal process; Composite material; Finite element method; Lubricant; Alloy; Thermocouple; Aluminium; Die (integrated circuit); Heat transfer; Heat transfer coefficient; Dwell time; Metallurgy; Compression (physics); Mechanics; Structural engineering; Thermodynamics","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":[0.0002649903,0.0001976351,0.0003413169,0.0001433528,0.00009054119,0.00006272266,0.0004135376,0.0001145128,0.0001023873],"category_scores_gemma":[0.0001787571,0.0002006729,0.00007163069,0.00006907329,0.00006009864,0.000685415,0.00009087403,0.0001261459,0.000005148609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005970327,"about_ca_system_score_gemma":0.00002362845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000129734,"about_ca_topic_score_gemma":0.000007793922,"domain_scores_codex":[0.9987621,0.000002500534,0.0005272762,0.0001848324,0.0002840199,0.0002393035],"domain_scores_gemma":[0.9989194,0.00005450982,0.000378625,0.0002503186,0.0003399797,0.00005719747],"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":[0.0001526234,0.0002521568,0.1209414,0.003023962,0.0003720708,0.00000292076,0.009241794,0.04336466,0.670854,0.02210467,0.0005613494,0.1291284],"study_design_scores_gemma":[0.0003625543,0.0001156541,0.005988164,0.000225339,0.00002919317,4.50455e-7,0.00006582633,0.7745541,0.2161175,0.001938905,0.000394409,0.0002078446],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9582044,0.00001230688,0.03714795,0.00003773242,0.0001211222,0.0003176249,0.00001371979,0.0001824823,0.003962705],"genre_scores_gemma":[0.9942079,0.00002472229,0.005499682,0.000008113959,0.00004597021,0.00002419806,0.000007972259,0.00003356841,0.0001479385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7311895,"threshold_uncertainty_score":0.8183202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02204458280093291,"score_gpt":0.2698744961962579,"score_spread":0.247829913395325,"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."}}