{"id":"W4387950884","doi":"10.1016/j.msea.2023.145844","title":"Revealing extraordinary work-hardening capacity in a high-entropy alloy with homogeneous composite structures","year":2023,"lang":"en","type":"article","venue":"Materials Science and Engineering A","topic":"High Entropy Alloys Studies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Materials science; Ultimate tensile strength; Alloy; Annealing (glass); Elongation; Work hardening; Composite number; Ductility (Earth science); Strengthening mechanisms of materials; Composite material; Homogeneous; Metallurgy; Hardening (computing); Precipitation hardening; Microstructure; Creep; Thermodynamics","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":[0.0003984315,0.0002201789,0.0002870941,0.0003413089,0.0001470234,0.0002357659,0.0001984395,0.00004525706,0.000007621279],"category_scores_gemma":[0.00004174657,0.0001949607,0.00001293271,0.0009776271,0.0001291802,0.0002722378,0.00009651866,0.0001099684,0.000009639942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001048523,"about_ca_system_score_gemma":0.00001409099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006574631,"about_ca_topic_score_gemma":0.000006438185,"domain_scores_codex":[0.9985854,0.00001170649,0.0002153863,0.0002899541,0.0003020191,0.0005955429],"domain_scores_gemma":[0.9996397,0.00003883431,0.00002120327,0.0001691899,0.00003630706,0.00009471683],"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":[0.000009873354,0.000002278303,0.0006441915,0.00008445405,0.00001207925,0.000068635,0.0004632674,0.2695151,0.7288918,0.0002236547,0.00003745326,0.00004714447],"study_design_scores_gemma":[0.001495025,0.0001831549,0.2880491,0.0009632122,0.00005653125,0.0002467807,0.0003204995,0.03838746,0.6676825,0.0001977107,0.0006904205,0.001727581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981678,0.0001229764,0.0004324822,0.00004295572,0.0004755894,0.0001361941,0.00001140892,0.0005934545,0.00001715332],"genre_scores_gemma":[0.9957602,0.00009086741,0.003966344,0.000008659339,0.00008424863,0.0000337068,0.000003778007,0.00003620024,0.00001600342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2874049,"threshold_uncertainty_score":0.7950267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01254740304206714,"score_gpt":0.1897444659393538,"score_spread":0.1771970628972867,"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."}}