{"id":"W2103594559","doi":"10.5267/j.ijiec.2013.04.002","title":"Optimization of multiple performance characteristics in turning using Taguchi’s quality loss function: An experimental investigation","year":2013,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Taguchi methods; Quality (philosophy); Function (biology); Computer science; Engineering; Control theory (sociology); Statistics; Mathematics; Artificial intelligence; Biology; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001028005,0.0005033708,0.0007547649,0.0005354089,0.0003361729,0.0004272615,0.0005891664,0.0007248655,0.0007057031],"category_scores_gemma":[0.001067289,0.0002799469,0.0004225802,0.0006292945,0.0005332512,0.0002593204,0.0003040617,0.0004467566,0.0001430248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002564048,"about_ca_system_score_gemma":0.0002175577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004715787,"about_ca_topic_score_gemma":0.0007506615,"domain_scores_codex":[0.999202,0.0001139875,0.000028939,0.00008811468,0.0003855612,0.000181437],"domain_scores_gemma":[0.9990634,0.0003893918,0.0001495983,0.0001508087,0.0001805318,0.0000662851],"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":[0.0006461095,0.0004302203,0.00112848,0.0001605183,0.00001819857,0.0001185823,0.0002447906,0.01150573,0.9691834,0.0002375266,0.00006854891,0.01625798],"study_design_scores_gemma":[0.00007707121,0.008333123,0.01150773,0.00001613507,0.00005492169,0.0001694622,0.000163739,0.03770292,0.9411443,0.0001029532,0.0006764848,0.00005094591],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900794,0.0001819781,0.008874163,0.00001647448,0.000009457818,0.00003882608,0.00003827499,0.00004278986,0.0007187139],"genre_scores_gemma":[0.9955075,0.0000889183,0.004005823,0.000005086656,0.000002672806,0.00001671039,0.00002142101,0.000008844465,0.0003430689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001028005,"threshold_uncertainty_score":0.005436659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03909334774248556,"score_gpt":0.2811338005585801,"score_spread":0.2420404528160945,"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."}}