{"id":"W2032166461","doi":"10.1361/105994902770343593","title":"Influence of the Post-Deformation Annealing Heat Treatment on the Low-Cycle Fatigue of NiTi Shape Memory Alloys","year":2002,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Shape Memory Alloy Transformations","field":"Materials Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Shape-memory alloy; Pseudoelasticity; SMA*; Nickel titanium; Annealing (glass); Differential scanning calorimetry; Composite material; Indentation hardness; Thermoelastic damping; Temperature cycling; Martensite; Metallurgy; Microstructure; Thermodynamics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000550838,0.00013594,0.00024766,0.00008157236,0.0001085705,0.00003699173,0.0002300769,0.00004422601,0.0001388687],"category_scores_gemma":[0.00006876967,0.00007345577,0.00005647128,0.00009890572,0.00005969993,0.0004724663,0.00002023296,0.00007685116,0.000006007087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003810559,"about_ca_system_score_gemma":0.00001906733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001391955,"about_ca_topic_score_gemma":6.910803e-7,"domain_scores_codex":[0.9988486,0.0000534438,0.000620366,0.00006410607,0.0002606455,0.0001528662],"domain_scores_gemma":[0.999244,0.000112859,0.0002844163,0.0001790515,0.0001405256,0.00003913126],"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":[0.00003595663,0.00002626594,0.00007389906,0.0001554405,0.00001130347,4.381974e-7,0.001400704,0.3086065,0.6894423,0.00002216088,0.000005646067,0.0002193874],"study_design_scores_gemma":[0.000341019,0.000330324,0.01269942,0.000476156,0.00002505091,0.00006288377,0.0000839261,0.02262078,0.9632505,0.000003058229,0.00002504756,0.00008188851],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991186,0.00009270805,0.0000170944,0.0002342365,0.0002959145,0.0001485947,0.00003299796,0.00001109184,0.00004879125],"genre_scores_gemma":[0.9994884,0.0002496515,0.0001169628,0.00004997303,0.00007069716,0.000005936922,8.233549e-7,0.00001014563,0.00000739581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2859857,"threshold_uncertainty_score":0.2995439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01690404945208436,"score_gpt":0.2101477408367105,"score_spread":0.1932436913846262,"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."}}