{"id":"W2002940584","doi":"10.4028/www.scientific.net/msf.519-521.1473","title":"Application of a Mathematical Model to Simulate Multi-Pass Hot Rolling of Aluminium Alloy AA5083","year":2006,"lang":"en","type":"article","venue":"Materials science forum","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Microstructure; Aluminium; Recrystallization (geology); Alloy; Thermal; Metallurgy; Dynamic recrystallization; Stored energy; First pass; Deformation (meteorology); Mechanics; Composite material; Thermodynamics; Hot working","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":[0.0005050198,0.0004745631,0.0007366272,0.000412917,0.0005395971,0.0007499419,0.0008680521,0.001508391,0.001619089],"category_scores_gemma":[0.001029826,0.0004154088,0.0009964334,0.0003522139,0.0004331207,0.000518321,0.000410031,0.0006417285,0.0002375671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008977944,"about_ca_system_score_gemma":0.001372395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01625637,"about_ca_topic_score_gemma":0.009340443,"domain_scores_codex":[0.9998722,0.00002972537,0.00001037612,0.00001740912,0.00004953376,0.00002063786],"domain_scores_gemma":[0.9995903,0.0002234246,0.00006101462,0.00002522556,0.00008730853,0.00001263995],"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":[0.000009240663,0.00001128931,0.0002375418,0.00001808454,0.000005713992,0.00003042008,0.0000151333,0.9963676,0.001288931,0.0009641309,0.00003744518,0.001014514],"study_design_scores_gemma":[0.000002676271,0.00001027018,0.00007469787,0.0000016617,0.000002277706,0.000004485883,0.000003135312,0.9993242,0.0003433293,0.0001029657,0.0001284422,0.000001886304],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3768417,0.00064586,0.6014274,0.0004732641,0.0001282335,0.0002737468,0.0005171041,0.0006279679,0.01906473],"genre_scores_gemma":[0.9501017,0.0003721717,0.04288823,0.00004350757,0.00001451442,0.0003141056,0.0002355564,0.00006307553,0.005967249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01625637,"threshold_uncertainty_score":0.03232348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01167993630489053,"score_gpt":0.2332627058544032,"score_spread":0.2215827695495127,"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."}}