{"id":"W3040126919","doi":"10.1016/j.mtla.2020.100812","title":"Use of in-situ laser-ultrasonics measurements to develop robust models combining deformation, recovery, recrystallization and grain growth","year":2020,"lang":"en","type":"article","venue":"Materialia","topic":"Metallurgy and Material Forming","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Recrystallization (geology); Dynamic recrystallization; Annealing (glass); Grain size; Stress relaxation; Flow stress; Laser ultrasonics; Grain growth; Metallurgy; Composite material; Hot working; Microstructure; Creep; Optoelectronics; Geology","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":[0.0002159165,0.0001189018,0.0001913943,0.00006858868,0.00002741396,0.00007707232,0.00006699828,0.00006227977,0.00002308964],"category_scores_gemma":[0.0001465553,0.0001264425,0.00001119834,0.0002301213,0.000007634159,0.0005558511,0.00004014685,0.00003231121,0.000007736723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003662709,"about_ca_system_score_gemma":0.00001373283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004060789,"about_ca_topic_score_gemma":0.00004397627,"domain_scores_codex":[0.9992211,0.00003488626,0.0003626612,0.0001134288,0.0001171024,0.0001508364],"domain_scores_gemma":[0.9997112,0.000005775968,0.00006162025,0.00007056785,0.00007921707,0.00007165888],"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":[0.0001511472,0.00001560927,0.0004984442,0.0007419453,0.00004519683,0.000002544097,0.003686584,0.1004246,0.8913642,0.001320581,0.001166072,0.000583093],"study_design_scores_gemma":[0.001231838,0.0001509615,0.002913173,0.0004831621,0.00004255864,0.000007707999,0.000207177,0.04540406,0.9441628,0.00143145,0.003238771,0.0007263094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9686574,0.000007297123,0.0297956,0.00004813696,0.0009209616,0.000211272,0.00001691186,0.00008466151,0.0002577394],"genre_scores_gemma":[0.9915653,0.00003443415,0.008177433,0.00008017843,0.00002303423,0.00001251251,0.00006645767,0.00002377376,0.00001689119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05502049,"threshold_uncertainty_score":0.5156175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08038506583305444,"score_gpt":0.2138365946295997,"score_spread":0.1334515287965453,"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."}}