{"id":"W3008869636","doi":"10.3390/jmmp4010016","title":"A Unique Methodology for Tool Life Prediction in Machining","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Rake; Flank; Machining; Tool wear; Face (sociological concept); von Mises yield criterion; Calibration; Finite element method; Computer science; Function (biology); Materials science; Mechanical engineering; Structural engineering; Mathematics; Engineering; Statistics","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":[0.000412369,0.0006390751,0.000529481,0.0007405521,0.0002696115,0.0003919609,0.0009723605,0.0007332244,0.001133999],"category_scores_gemma":[0.001053604,0.0003395424,0.0006310293,0.0005253347,0.0002881099,0.000675879,0.0003997847,0.0006726044,0.0004865807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002191568,"about_ca_system_score_gemma":0.0004025326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001000288,"about_ca_topic_score_gemma":0.001013194,"domain_scores_codex":[0.9996685,0.000043119,0.0000185873,0.00007000012,0.0001833702,0.00001638441],"domain_scores_gemma":[0.9996027,0.0001327508,0.00005026499,0.00007492991,0.0001284377,0.00001089415],"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":[0.00003106722,0.00008413867,0.002425085,0.0005209657,0.00008188971,0.0001165114,0.000202352,0.5289751,0.06091959,0.02053352,0.001465199,0.3846447],"study_design_scores_gemma":[0.000003816816,0.00006289809,0.0005157724,0.00001827094,0.00001073334,0.000118681,0.00001676295,0.9819998,0.008344094,0.002966789,0.00592669,0.00001564517],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002529203,0.0001084126,0.996474,0.000008933273,0.00001561202,0.00002169737,0.00002022007,0.0002520503,0.0005699092],"genre_scores_gemma":[0.2695065,0.0006068983,0.7260192,0.00005349858,0.00005121679,0.0003065985,0.0002744129,0.0001776205,0.003003964],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001133999,"threshold_uncertainty_score":0.003793657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03854059991764456,"score_gpt":0.2686314966079568,"score_spread":0.2300908966903123,"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."}}