{"id":"W2528880305","doi":"10.1016/j.precisioneng.2016.09.021","title":"Modeling dynamics and stability of variable pitch and helix milling tools for development of a design method to maximize chatter stability","year":2016,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Pratt and Whitney Canada","keywords":"Stability (learning theory); Machinability; Variable (mathematics); Discretization; Focus (optics); Machine tool; Computer science; Control theory (sociology); Machining; Engineering; Mechanical engineering; Mathematics; Artificial intelligence; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005587579,0.0005195905,0.0004391696,0.0003293335,0.0003861308,0.0005350755,0.0006809598,0.0006958605,0.001793323],"category_scores_gemma":[0.0009690002,0.0003945472,0.0005323112,0.0002384673,0.0003818539,0.0006660596,0.0003844042,0.0005217593,0.0002575429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004614688,"about_ca_system_score_gemma":0.000681651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003172107,"about_ca_topic_score_gemma":0.003692069,"domain_scores_codex":[0.999878,0.00003381806,0.000005877707,0.00002260423,0.00004790778,0.00001179292],"domain_scores_gemma":[0.9997106,0.0001649206,0.00004528078,0.00001557332,0.0000543472,0.000009271412],"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":[0.00002206896,0.000017534,0.0002209278,0.00005347112,0.00001037079,0.00002409888,0.00006327908,0.9765237,0.009671586,0.005935187,0.0001082959,0.007349483],"study_design_scores_gemma":[0.000001938883,0.00000915925,0.00003292718,0.00000229472,0.000002134871,0.00000345632,0.000003607142,0.9985171,0.0008627358,0.0004224675,0.000140551,0.000001654407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02715326,0.0001250195,0.9696372,0.00004490841,0.00001337214,0.00003145658,0.00001501198,0.00007604645,0.002903712],"genre_scores_gemma":[0.8955271,0.0002573625,0.09921465,0.00002589402,0.00001286172,0.000150346,0.00003709483,0.00004948409,0.004725292],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003172107,"threshold_uncertainty_score":0.006307244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03839781086723889,"score_gpt":0.2626858678034849,"score_spread":0.224288056936246,"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."}}