{"id":"W2029359094","doi":"10.1007/s11837-009-0117-4","title":"Microstructure and temperature monitoring during the hot rolling of AZ31","year":2009,"lang":"en","type":"article","venue":"JOM","topic":"Magnesium Alloys: Properties and Applications","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Microstructure; Materials science; Recrystallization (geology); Dynamic recrystallization; Metallurgy; Grain size; Rolling mill; Deformation (meteorology); Alloy; Hot working; Strain rate; Composite material; Mechanical engineering; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00006713333,0.00006271862,0.00007902276,0.00001140767,0.000186909,0.00006736284,0.0001246672,0.00003763704,0.00004229766],"category_scores_gemma":[0.000009347274,0.00003711847,0.00001830272,0.00005965702,0.00003484156,0.0000572294,0.00002837326,0.00006690517,0.000003345956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006537108,"about_ca_system_score_gemma":0.000009261921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002382203,"about_ca_topic_score_gemma":0.00000233169,"domain_scores_codex":[0.9995744,0.00001188673,0.0001072837,0.0001199208,0.00007791456,0.0001085426],"domain_scores_gemma":[0.9997198,0.00001377844,0.00004452775,0.0001710491,0.00002710481,0.00002376723],"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":[0.00000963274,0.000004649678,0.0006137741,0.00001790425,6.957599e-7,3.741461e-7,0.0002494457,0.00004679373,0.9986861,0.0001204739,0.00002740292,0.0002226984],"study_design_scores_gemma":[0.0001036719,0.00001707787,0.1207409,0.00001923841,0.000005955196,0.000008307173,0.0001871151,0.00001393425,0.8781315,0.0001475299,0.0005648497,0.00005992933],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985066,0.0005815953,0.000002776402,0.0005347691,0.00008835983,0.00009108378,0.000005927467,0.00002108601,0.0001677863],"genre_scores_gemma":[0.998661,0.00004629611,0.0006994337,0.00004665016,0.0001847668,0.000004632796,3.964741e-7,0.000004227451,0.0003526248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1205547,"threshold_uncertainty_score":0.1513647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006556079705664288,"score_gpt":0.2148159423037332,"score_spread":0.2082598625980689,"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."}}