{"id":"W2091014384","doi":"10.1007/s11740-009-0177-x","title":"Optimization of surface roughness in an end-milling operation using nested experimental design","year":2009,"lang":"en","type":"article","venue":"Production Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Machining; Surface roughness; Materials science; Aluminium; Surface finish; Metallurgy; Taguchi methods; Carbon steel; Alloy; Aluminium alloy; Composite material; Mechanical engineering; Engineering","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":[0.002082773,0.0006424142,0.0009731459,0.0003052552,0.0004578055,0.0008051605,0.0008563901,0.0006733282,0.0007812652],"category_scores_gemma":[0.002896831,0.0005461788,0.0006198307,0.0002229575,0.0007015908,0.000878242,0.0006943233,0.0006617325,0.0000794786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007062114,"about_ca_system_score_gemma":0.0009799943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00134318,"about_ca_topic_score_gemma":0.001929158,"domain_scores_codex":[0.9991881,0.0002372421,0.00004166125,0.0001384821,0.0002889391,0.0001055305],"domain_scores_gemma":[0.9982936,0.0009622268,0.0002417761,0.000170391,0.0002746308,0.00005736807],"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":[0.0008206079,0.0005865552,0.00140829,0.0001727835,0.00004275021,0.00004590033,0.0001019947,0.8627598,0.1085471,0.002017634,0.00009314415,0.02340339],"study_design_scores_gemma":[0.0000561274,0.0006069734,0.0006442462,0.000003420089,0.00001750148,0.000009550393,0.00001368017,0.9721152,0.02605007,0.0003072905,0.0001630012,0.00001301074],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6839566,0.0001324982,0.3128532,0.00005566098,0.00002575485,0.0001766436,0.00004183694,0.0001981063,0.002559674],"genre_scores_gemma":[0.9385645,0.00002529745,0.06095101,0.000008357828,0.000002794571,0.0000839839,0.000021466,0.00002249617,0.0003200803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002082773,"threshold_uncertainty_score":0.01101494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02204599708791042,"score_gpt":0.2580967823862313,"score_spread":0.2360507852983209,"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."}}