{"id":"W3043735498","doi":"10.1115/1.4047391","title":"Chatter Stability of Machining Operations","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Science Foundation of Sri Lanka; Natural Sciences and Engineering Research Council of Canada; American Research Institute in Turkey","keywords":"Machining; Stability (learning theory); Engineering; Coupling (piping); Process (computing); Computer science; Mechanical engineering; Control theory (sociology); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002480325,0.00007126344,0.0001280875,0.00008905328,0.00004652179,0.00003611355,0.0001256443,0.00001719372,0.000007743432],"category_scores_gemma":[0.0001162282,0.00006250329,0.00002027963,0.0001365171,0.00003739125,0.0005483447,0.0000252975,0.0001433622,2.599056e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002384321,"about_ca_system_score_gemma":0.00001984307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001019649,"about_ca_topic_score_gemma":2.087528e-7,"domain_scores_codex":[0.9993907,0.00000214063,0.0002286212,0.00006986449,0.0001924889,0.0001161489],"domain_scores_gemma":[0.999727,0.00002030838,0.00003556442,0.00004813091,0.0000728222,0.00009619264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002497535,0.000002167581,0.0001391327,0.0001119516,0.000005268207,0.000001199472,0.0008245039,0.9689927,0.02734421,0.00002161275,0.000003652824,0.002551107],"study_design_scores_gemma":[0.0001715059,0.00005987552,0.003544338,0.00006491204,0.00001036686,0.00001948703,0.0001325599,0.6255941,0.3700478,0.00001115194,0.0002347288,0.0001091679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8474454,0.0001873088,0.1519933,0.000119096,0.0001267749,0.00002447862,8.475635e-7,0.00002858127,0.00007413282],"genre_scores_gemma":[0.9858572,0.00008108746,0.01395966,0.00003378647,0.00005900775,3.692814e-7,1.419282e-7,0.00000830278,3.895027e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3433986,"threshold_uncertainty_score":0.254881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185960391980941,"score_gpt":0.2121628403949689,"score_spread":0.2003032364751595,"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."}}