{"id":"W2758971340","doi":"10.1016/j.ijplas.2017.09.013","title":"Experimental analyses and numerical modeling of texture evolution and the development of surface roughness during bending of an extruded aluminum alloy using a multiscale modeling framework","year":2017,"lang":"en","type":"article","venue":"International Journal of Plasticity","topic":"Metal Forming Simulation Techniques","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada","keywords":"Materials science; Alloy; Surface roughness; Surface finish; Texture (cosmology); Aluminium; Bending; Surface (topology); Composite material; Metallurgy; Geometry; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000164988,0.0001532052,0.0001832451,0.0001900632,0.0001884176,0.0002478583,0.0003223704,0.0003408134,0.0006158422],"category_scores_gemma":[0.0004761268,0.0001736036,0.00016742,0.0001827745,0.0003068308,0.0002033711,0.0001515805,0.0002298172,0.00006973797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002523125,"about_ca_system_score_gemma":0.0001595529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001668008,"about_ca_topic_score_gemma":0.001607963,"domain_scores_codex":[0.9999192,0.000008770287,0.000004877537,0.00001337859,0.0000392988,0.00001447326],"domain_scores_gemma":[0.9997929,0.00007714137,0.00003896991,0.00003752245,0.00004231717,0.00001120002],"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":[0.0002250841,0.0001508109,0.003150532,0.00006486768,0.000009633604,0.0001472257,0.0001432731,0.05517918,0.9325541,0.0008331869,0.0001094747,0.007432621],"study_design_scores_gemma":[0.00002279868,0.0003389445,0.02106797,0.000005583008,0.00001673007,0.0001154714,0.00009812059,0.6858884,0.2918218,0.0001873283,0.0004091634,0.00002757404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948014,0.00005119362,0.004536462,0.00002201726,0.000004849057,0.000006932863,0.00003977625,0.00004845094,0.0004889586],"genre_scores_gemma":[0.9988991,0.0000163599,0.0009676486,0.000001507156,0.000001139066,0.000002840124,0.00001281965,0.000003742562,0.00009483974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001668008,"threshold_uncertainty_score":0.003316641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05050116945100071,"score_gpt":0.3515578776237391,"score_spread":0.3010567081727384,"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."}}