{"id":"W2608335530","doi":"10.1007/s11837-017-2339-1","title":"Constitutive Relations Analyses of Plastic Flow in Dual-Phase Steels to Elucidate Structure–Strength–Ductility Correlations","year":2017,"lang":"en","type":"article","venue":"JOM","topic":"Microstructure and mechanical properties","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Plasticity; Ultimate tensile strength; Constitutive equation; Mesoscopic physics; Work hardening; Strain hardening exponent; Ductility (Earth science); Flow stress; Microstructure; Substructure; Structural material; Slip (aerodynamics); Dual-phase steel; Hardening (computing); Composite material; Structural engineering; Thermodynamics; Martensite; Physics; Condensed matter physics; Finite element method; Engineering","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":[0.0003076213,0.0002978843,0.000208316,0.001183969,0.0002022478,0.0003301288,0.0003872941,0.000303969,0.001050734],"category_scores_gemma":[0.0007296796,0.0002598121,0.0003096693,0.0004555761,0.0002566345,0.0004531069,0.0002008909,0.0003341005,0.0001809699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000444818,"about_ca_system_score_gemma":0.0003732675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001431497,"about_ca_topic_score_gemma":0.003804286,"domain_scores_codex":[0.9998949,0.00001656096,0.000006203631,0.00002154373,0.00004717266,0.0000136762],"domain_scores_gemma":[0.9997076,0.00009009735,0.00007762227,0.00003533685,0.00007557595,0.0000137688],"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":[0.0001236831,0.0003066883,0.01231444,0.0001391288,0.00005555259,0.0002238594,0.0001438034,0.2513035,0.6858261,0.02018584,0.0006784001,0.02869903],"study_design_scores_gemma":[0.000007418089,0.00004751416,0.01025417,0.00000695752,0.00001474442,0.00006218303,0.000029178,0.9465258,0.04029308,0.001821506,0.000924987,0.00001261462],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8464032,0.0003584544,0.1448246,0.000165651,0.00002187589,0.00005170071,0.0003453645,0.0003193582,0.007509651],"genre_scores_gemma":[0.9911335,0.0000813462,0.007492177,0.00001264321,0.000005119685,0.00001715213,0.0001289077,0.0000218775,0.001107285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001431497,"threshold_uncertainty_score":0.003515065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05645820175955985,"score_gpt":0.3582560255392451,"score_spread":0.3017978237796852,"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."}}