{"id":"W4407058689","doi":"10.1016/j.jmrt.2025.01.246","title":"Optimising subsurface integrity and surface quality in mild steel turning: A multi-objective approach to tool wear and machining parameters","year":2025,"lang":"en","type":"article","venue":"Journal of Materials Research and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Mechanical Engineering, University of Alberta; State Key Laboratory of Tribology; Tsinghua University","keywords":"Materials science; Surface integrity; Machining; Metallurgy; Quality (philosophy); Tool wear; Mechanical engineering; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007011807,0.0008269602,0.0007009295,0.0006223723,0.0002205723,0.0006890978,0.0005032627,0.0005631577,0.000347234],"category_scores_gemma":[0.0007376644,0.0003252153,0.0007517579,0.0003057031,0.0002642094,0.0003498846,0.0003403637,0.0003269796,0.00005255009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000328156,"about_ca_system_score_gemma":0.0005564571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002465996,"about_ca_topic_score_gemma":0.003340165,"domain_scores_codex":[0.99972,0.00005657226,0.00001875497,0.00005601025,0.0001050599,0.00004355988],"domain_scores_gemma":[0.9996958,0.0001300555,0.000076278,0.00001748249,0.00006635951,0.00001408256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001717254,0.0002131379,0.006130089,0.0003364345,0.0001290017,0.0001073253,0.0001494631,0.7862054,0.1276996,0.0005411758,0.0001353782,0.07818139],"study_design_scores_gemma":[0.00001695587,0.0005596768,0.006855829,0.00001135608,0.00007184048,0.00004037384,0.00008202783,0.9773616,0.01438629,0.0002983746,0.0002943587,0.00002123662],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6520357,0.000597801,0.3454463,0.00006640523,0.00001551914,0.0001042974,0.00005461017,0.0001843107,0.001495063],"genre_scores_gemma":[0.952072,0.00009107686,0.04721044,0.00001629813,0.000004550118,0.00005852302,0.00004877132,0.00002031854,0.0004780919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002465996,"threshold_uncertainty_score":0.004903316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05218484253587878,"score_gpt":0.3626341942628321,"score_spread":0.3104493517269533,"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."}}