{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006625758,0.0004584136,0.0005140253,0.0004855401,0.0002363829,0.0009163513,0.0006524928,0.0003962965,0.002630025],"category_scores_gemma":[0.00280769,0.0001447391,0.0003305489,0.0002244868,0.001106239,0.0008492796,0.0005956384,0.0007476581,0.0003560878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005965314,"about_ca_system_score_gemma":0.000367623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00105458,"about_ca_topic_score_gemma":0.0004410658,"domain_scores_codex":[0.9993201,0.0001245092,0.00002696018,0.0001367652,0.0003365919,0.00005513414],"domain_scores_gemma":[0.9985983,0.0006794771,0.0002258093,0.0001535372,0.0003065201,0.00003637694],"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":[0.0003512576,0.00007406889,0.002485819,0.0004956054,0.0000819227,0.0004798916,0.0008082127,0.4324375,0.07849744,0.4134952,0.001712798,0.06908033],"study_design_scores_gemma":[0.000009086569,0.00009948757,0.0007671178,0.0000260092,0.000007613619,0.0001333658,0.00005682091,0.9314522,0.007222189,0.05839572,0.001812989,0.00001745256],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.113626,0.001663539,0.8599357,0.0002979851,0.0001138331,0.00004642129,0.00006267158,0.0003690602,0.02388484],"genre_scores_gemma":[0.9808781,0.0004275193,0.01343741,0.00004463077,0.00004619953,0.00003325673,0.00003931687,0.00003855839,0.005055015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002630025,"threshold_uncertainty_score":0.008798301,"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."}}