{"id":"W7083578076","doi":"10.1016/j.msea.2025.149180","title":"Achieving excellent strength-ductility synergy in TWIP-assisted Fe25CoxCr25Ni50-x high-entropy alloys via Co/Ni ratio and stacking fault energy manipulation","year":2025,"lang":"en","type":"article","venue":"Materials Science and Engineering A","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Education and Child Care","funders":"Central South University; Yunnan Provincial Department of Education Science Research Fund Project; National Natural Science Foundation of China","keywords":"Stacking-fault energy; Ultimate tensile strength; Stacking; Annealing (glass); Strengthening mechanisms of materials; Ductility (Earth science); Alloy; Stacking fault","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001111304,0.0002125956,0.00026716,0.0004745537,0.0002207819,0.0007029806,0.003417912,0.00009582548,0.000005368658],"category_scores_gemma":[0.002271812,0.0002096159,0.00001243586,0.0008602687,0.0001676176,0.00111792,0.008530788,0.0001104883,9.642541e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001905636,"about_ca_system_score_gemma":0.00007228629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006380873,"about_ca_topic_score_gemma":0.00002591415,"domain_scores_codex":[0.9980421,0.00005212271,0.0003798371,0.0007176886,0.0003477959,0.000460439],"domain_scores_gemma":[0.9980268,0.00008917235,0.00008703912,0.001660779,0.00006920264,0.00006698923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008772213,0.00003531777,0.0007084224,0.0001011388,0.000009347918,0.00001208635,0.00008250543,0.000876617,0.9686593,0.01766309,0.0002533743,0.01158996],"study_design_scores_gemma":[0.0005640449,0.00006222376,0.0829882,0.0002947897,0.000009577163,0.00002084575,0.00005321465,0.5405175,0.3675554,0.006814227,0.0006250467,0.0004949549],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8018649,0.0001204603,0.1955232,0.001368472,0.0006785291,0.00009734802,0.000005918629,0.0003164695,0.0000247142],"genre_scores_gemma":[0.9662443,0.000107936,0.03352545,0.00004504521,0.00002460668,0.00002490565,0.000007849638,0.00000779994,0.00001207071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.601104,"threshold_uncertainty_score":0.9994881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01359054571415989,"score_gpt":0.2369337580779601,"score_spread":0.2233432123638003,"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."}}