{"id":"W2248088928","doi":"10.4271/2004-01-0742","title":"Multi-Scale FE/Damage Percolation Modeling of Ductile Damage Evolution in Aluminum Sheet Forming","year":2004,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Metal Forming Simulation Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Percolation (cognitive psychology); Materials science; Aluminium; Scale (ratio); Composite material; Physics","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":[0.0001566437,0.0002815816,0.0002835371,0.0003623259,0.0002912726,0.0003289795,0.0005835515,0.0007267188,0.001001464],"category_scores_gemma":[0.0004055152,0.0003034154,0.0002904493,0.0002635716,0.0004655735,0.000382893,0.0003122331,0.0002355406,0.00009798291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006756603,"about_ca_system_score_gemma":0.0002779191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009081892,"about_ca_topic_score_gemma":0.006300936,"domain_scores_codex":[0.9999362,0.00001699582,0.000002995995,0.00001216496,0.00001947483,0.00001223036],"domain_scores_gemma":[0.9998438,0.00006878308,0.0000278988,0.00001988266,0.00002250787,0.00001705026],"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":[0.00001500528,0.00001456625,0.0006896878,0.000007188477,0.00000548748,0.00006339917,0.00003231165,0.9930336,0.004046112,0.0006882509,0.00005692964,0.001347464],"study_design_scores_gemma":[0.000001156813,0.000004153986,0.0002605542,5.172291e-7,9.13612e-7,0.000008389513,0.000004504669,0.9991193,0.0004179087,0.0001363517,0.00004470613,0.000001448516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9032055,0.0001546173,0.08871202,0.0001216687,0.00001346149,0.00003508969,0.0001005034,0.0003966873,0.007260549],"genre_scores_gemma":[0.994831,0.00003045159,0.004373267,0.000009290675,0.000002012953,0.00001031266,0.00001784601,0.00001894652,0.0007068478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009081892,"threshold_uncertainty_score":0.01805806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01493243727469003,"score_gpt":0.2516564426578118,"score_spread":0.2367240053831218,"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."}}