{"id":"W2789562706","doi":"10.3390/jmmp2010016","title":"Prediction and Optimization of Drilling Parameters in Drilling of AISI 304 and AISI 2205 Steels with PVD Monolayer and Multilayer Coated Drills","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced Machining and Optimization Techniques","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Materials science; Taguchi methods; Machining; Metallurgy; Drilling; Work hardening; Tool wear; Tin; Austenitic stainless steel; Composite material; Corrosion; Microstructure","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":[0.0006040524,0.0006151833,0.0005446328,0.0006755408,0.000150671,0.0005639225,0.0002693751,0.0006832721,0.0001831698],"category_scores_gemma":[0.00106715,0.0004254378,0.0004545262,0.0003875042,0.000212403,0.0003328758,0.0001636895,0.0002779779,0.0001213495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000362662,"about_ca_system_score_gemma":0.0005333534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002502556,"about_ca_topic_score_gemma":0.005069186,"domain_scores_codex":[0.9997117,0.00004530947,0.00003535128,0.00005455221,0.0001094044,0.00004362579],"domain_scores_gemma":[0.9993472,0.0002729246,0.0001962043,0.00002442111,0.0001263806,0.00003292996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007710258,0.0003720853,0.02269817,0.0005861662,0.00006416026,0.0002005859,0.0001831452,0.2972806,0.6275296,0.0002307243,0.0002206734,0.049863],"study_design_scores_gemma":[0.00004916127,0.002081277,0.04152364,0.0000282972,0.0001281582,0.0001362752,0.0002264529,0.6405557,0.3142993,0.0001707488,0.0007179419,0.00008303409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791117,0.0003266261,0.02000869,0.00001495283,0.000005677694,0.00003197188,0.00007857296,0.00006899541,0.0003527764],"genre_scores_gemma":[0.9860167,0.0001602476,0.01348215,0.000005264362,0.000001075489,0.00002402275,0.00008222598,0.000009685016,0.0002186724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002502556,"threshold_uncertainty_score":0.004975975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01007849987507647,"score_gpt":0.2189845622907313,"score_spread":0.2089060624156549,"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."}}