{"id":"W2219668629","doi":"10.1016/j.actamat.2015.04.037","title":"Microstructural evolution during non-isothermal annealing of a precipitation-hardenable aluminum alloy: Experiment and simulation","year":2015,"lang":"en","type":"article","venue":"Acta Materialia","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Novelis (Canada); McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Annealing (glass); Isothermal process; Recrystallization (geology); Alloy; Monte Carlo method; Precipitation; Aluminium; Metallurgy; Dynamic recrystallization; Precipitation hardening; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009932219,0.0001914458,0.0002142761,0.00007173313,0.00005391593,0.0000820904,0.0001033123,0.00009509438,0.00005042196],"category_scores_gemma":[0.00002272193,0.0001856927,0.00002595817,0.00006065043,0.00006301286,0.0003941802,0.00006248963,0.0000521768,0.000007140849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000148983,"about_ca_system_score_gemma":0.00002092883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001124861,"about_ca_topic_score_gemma":0.0000049879,"domain_scores_codex":[0.9990895,0.00002621459,0.0003147007,0.0001817204,0.0001481089,0.0002396987],"domain_scores_gemma":[0.9995746,0.000006937824,0.00007665244,0.0001769392,0.00008943587,0.00007540374],"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":[0.00009925615,0.000003856233,0.0007777728,0.0001382549,0.00003354987,0.00000108451,0.00387425,0.01500981,0.9798602,0.00000661214,0.0001679862,0.00002737863],"study_design_scores_gemma":[0.001056142,0.00005564804,0.01606472,0.00006716619,0.00002524897,0.00001829113,0.0006319488,0.0287878,0.9525561,0.00009251192,0.0003451026,0.0002993397],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976779,0.0002550997,0.0001268271,0.00001220535,0.001469023,0.0002483336,0.00002374652,0.0001250648,0.00006186342],"genre_scores_gemma":[0.9978462,0.000004975875,0.001731344,0.000004498827,0.0001687414,0.00001666585,0.00002205153,0.00005150729,0.0001540568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02730412,"threshold_uncertainty_score":0.7572327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01110433541867581,"score_gpt":0.2224828021234589,"score_spread":0.2113784667047831,"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."}}