{"id":"W2042040976","doi":"10.4028/www.scientific.net/kem.261-263.1129","title":"Dynamic Strain Aging during Low Cycle Fatigue Deformation in Prior Cold Worked 316L Stainless Steel","year":2004,"lang":"en","type":"article","venue":"Key engineering materials","topic":"Microstructure and Mechanical Properties of Steels","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Materials science; Dynamic strain aging; Softening; Low-cycle fatigue; Strain rate; Deformation (meteorology); Strain (injury); Composite material; Plateau (mathematics); Metallurgy; Stress (linguistics); Atmospheric temperature range; Plasticity; Amplitude; Ultimate tensile strength; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000286669,0.0002316758,0.0003220218,0.0003652584,0.0002536273,0.0001672968,0.0002456984,0.0003256649,0.0008595397],"category_scores_gemma":[0.0006009134,0.0001919548,0.0001958156,0.0002454149,0.0003291279,0.0002812999,0.0001724615,0.0002130161,0.0001570431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000409288,"about_ca_system_score_gemma":0.0001516102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002604562,"about_ca_topic_score_gemma":0.004755414,"domain_scores_codex":[0.9997279,0.00002754894,0.00001954478,0.00006148528,0.0001151059,0.00004833824],"domain_scores_gemma":[0.9994555,0.0000762671,0.0001068818,0.00005331302,0.0002624365,0.00004560957],"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":[0.0001570807,0.00001445402,0.003395293,0.00004287124,0.000005510499,0.00009979944,0.00008562608,0.0003264169,0.9937738,0.00001559053,0.00002574772,0.002057785],"study_design_scores_gemma":[0.00001143675,0.0009384893,0.09339871,0.000009698984,0.00002066831,0.0002986983,0.0001129713,0.002244137,0.9022642,0.00002789912,0.0006521369,0.00002103303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991015,0.0001813165,0.0004309915,0.000008103289,0.000003238814,0.000005509509,0.00006885851,0.00001346187,0.0001870455],"genre_scores_gemma":[0.9991283,0.00005463587,0.0003071298,0.00001070736,0.000002584139,0.000006679628,0.0001107589,0.000005906541,0.0003732456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002604562,"threshold_uncertainty_score":0.00517875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004716340642587301,"score_gpt":0.1853984248365527,"score_spread":0.1806820841939654,"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."}}