{"id":"W2553954891","doi":"10.1007/s00170-016-9757-z","title":"A spline-based method for stability analysis of milling processes","year":2016,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"National Institute for Materials Science; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Floquet theory; Collocation method; Mathematics; Stability (learning theory); Chebyshev filter; Spline (mechanical); Control theory (sociology); B-spline; Applied mathematics; Mathematical analysis; Computer science; Differential equation; Engineering; Nonlinear system; Ordinary differential equation; Structural engineering; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002736574,0.0001112682,0.0002705006,0.0005252626,0.0000299335,0.000008680034,0.0005640492,0.00006217416,0.00001602921],"category_scores_gemma":[0.0004745001,0.0000660265,0.0001189159,0.0002819439,0.00005749044,0.0001524093,0.00003424565,0.0001077975,1.868534e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008765435,"about_ca_system_score_gemma":0.00004247549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001210267,"about_ca_topic_score_gemma":0.00001477082,"domain_scores_codex":[0.9991182,0.000008084248,0.0004494682,0.000106805,0.0001888204,0.0001286097],"domain_scores_gemma":[0.9983823,0.0005440256,0.0003565795,0.0001584171,0.0005382887,0.00002041095],"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":[0.0001485335,0.00001910278,0.00007754646,0.00004966826,0.0005032661,0.00000116176,0.00003760479,0.8968757,0.03348549,0.0002642543,0.00000458258,0.0685331],"study_design_scores_gemma":[0.0006572605,0.00008718475,0.00007454676,0.00009560445,0.000203999,0.000007684233,0.00006927427,0.03831155,0.9491144,0.01024471,0.001042132,0.0000916188],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2301105,0.0002300063,0.7683228,0.0009790272,0.0001878753,0.00007225251,0.00002254375,0.00006225612,0.00001274631],"genre_scores_gemma":[0.7631543,0.0001813573,0.2365771,0.00002268696,0.00003440968,0.000009419022,0.000002206152,0.00001388792,0.000004696948],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.915629,"threshold_uncertainty_score":0.2692482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01120926237138364,"score_gpt":0.2813953592525026,"score_spread":0.2701860968811189,"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."}}