{"id":"W4285405289","doi":"10.1016/j.jmrt.2022.07.036","title":"Constitutive analysis of stress–strain curves in dynamic softening of high Nb- and N-containing austenitic stainless-steel biomaterial","year":2022,"lang":"en","type":"article","venue":"Journal of Materials Research and Technology","topic":"Metallurgy and Material Forming","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Materials science; Isothermal process; Austenitic stainless steel; Softening; Dynamic recrystallization; Stacking-fault energy; Work hardening; Strain rate; Metallurgy; Composite material; Hot working; Thermodynamics; Corrosion; Microstructure","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":[0.001738298,0.0001111701,0.0007282338,0.002212992,0.00007723986,0.00002256778,0.0002006892,0.00009663089,0.0001649626],"category_scores_gemma":[0.0002092869,0.0001029211,0.00003182681,0.0008097072,0.0004147198,0.0001263246,0.0002245576,0.0002251194,1.464106e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006018527,"about_ca_system_score_gemma":0.0000723303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007686156,"about_ca_topic_score_gemma":0.00004276414,"domain_scores_codex":[0.9984201,0.0001707799,0.0007259039,0.0001193228,0.0002715268,0.0002923473],"domain_scores_gemma":[0.9993058,0.0001382341,0.000226112,0.0001144908,0.0001680261,0.00004729917],"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":[0.0003416636,0.00004177033,0.0006217921,0.000628681,0.0005116643,0.000144299,0.0001904219,0.0005209771,0.9913427,0.00475272,0.000002934778,0.000900382],"study_design_scores_gemma":[0.002995588,0.002328299,0.006555845,0.00101032,0.0004098196,0.0004217597,0.00690025,0.0009241503,0.9677272,0.01027578,0.0001042564,0.0003466787],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980369,0.001008776,0.00006765719,0.00008053582,0.0002143047,0.0001299612,0.0004241928,0.00001569825,0.0000219786],"genre_scores_gemma":[0.9989183,0.0007078541,0.0003094342,0.000001925671,0.00001331352,0.00001240097,0.00002046186,0.00001104571,0.00000525321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02361545,"threshold_uncertainty_score":0.4197001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02002236034069929,"score_gpt":0.2957333276111894,"score_spread":0.2757109672704901,"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."}}