{"id":"W2068824918","doi":"10.1016/j.ijmecsci.2014.12.002","title":"Numerical study of the effects of shear deformation and superimposed hydrostatic pressure on the formability of AZ31B sheet at room temperature","year":2014,"lang":"en","type":"article","venue":"International Journal of Mechanical Sciences","topic":"Magnesium Alloys: Properties and Applications","field":"Materials Science","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy","keywords":"Formability; Materials science; Necking; Forming limit diagram; Hydrostatic pressure; Crystal twinning; Shear (geology); Deformation (meteorology); Hydrostatic equilibrium; Plasticity; Metallurgy; Composite material; Mechanics; Microstructure","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":[0.001368406,0.00007166657,0.0001784704,0.00003283045,0.0001228721,0.00003513003,0.0007495697,0.0000318058,0.00006886476],"category_scores_gemma":[0.0007010828,0.0000312455,0.00006326241,0.0001236751,0.0001899069,0.0001745303,0.000142507,0.0000939974,7.296209e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001812563,"about_ca_system_score_gemma":0.00003853544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000700157,"about_ca_topic_score_gemma":0.00000982023,"domain_scores_codex":[0.9982017,0.00023881,0.0004845571,0.0001078295,0.0008796555,0.00008740176],"domain_scores_gemma":[0.9985865,0.0005404428,0.000453205,0.0001415376,0.0002410861,0.00003722022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001616044,0.0004643832,0.001569501,0.00006401302,0.0000218693,2.430279e-7,0.001389036,0.001559115,0.9866755,0.007529277,0.0000567548,0.0005086947],"study_design_scores_gemma":[0.0009741888,0.003302107,0.03083806,0.0001800704,0.00006551385,0.00002944109,0.001023639,0.01310009,0.9464945,0.003732997,0.0001568035,0.0001026491],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978724,0.00003323717,0.00008874844,0.001398377,0.0002816212,0.00024169,0.00000595042,0.000002184261,0.00007580742],"genre_scores_gemma":[0.999719,0.000005205158,0.0001405326,0.00008403652,0.00003378966,0.000005566641,1.641797e-7,0.000002196346,0.000009523161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04018106,"threshold_uncertainty_score":0.1392899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0096873789049402,"score_gpt":0.247154627185921,"score_spread":0.2374672482809808,"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."}}