{"id":"W4312419131","doi":"10.1115/msec2022-85157","title":"Estimating Milling Forces From Vibration Measurements","year":2022,"lang":"en","type":"article","venue":"Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Acceleration; Vibration; Accelerometer; Machining; Kalman filter; Deconvolution; Acoustics; Filter (signal processing); Control theory (sociology); Computer science; Engineering; Mechanical engineering; Physics; Computer vision; Algorithm; Artificial intelligence","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.00082801,0.002337364,0.001618664,0.001538862,0.002565377,0.001036103,0.001389024,0.0004898859,0.001397714],"category_scores_gemma":[0.000124702,0.00268149,0.0005332817,0.0003439971,0.000199415,0.002384423,0.001315178,0.001757295,0.0001155934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001430258,"about_ca_system_score_gemma":0.0001328655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002511803,"about_ca_topic_score_gemma":0.00002049276,"domain_scores_codex":[0.9907514,0.0002103397,0.002295155,0.002366748,0.001909982,0.002466372],"domain_scores_gemma":[0.996282,0.0004622487,0.0009592482,0.001234382,0.0001034379,0.0009586736],"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":[0.0001134534,0.0001451447,0.0001345508,0.0006677432,0.000700674,0.00005678025,0.001298207,0.9493704,0.01455446,0.00001756892,0.0006243011,0.03231673],"study_design_scores_gemma":[0.002406744,0.0002154417,0.007895706,0.0003340015,0.0002614963,0.00007856694,0.0004035453,0.2096878,0.7622111,0.0005807082,0.01306248,0.002862425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8887314,0.00120778,0.09794711,0.0002209505,0.004398329,0.001724454,0.0008555222,0.00436558,0.0005489092],"genre_scores_gemma":[0.9561096,0.000233095,0.03867758,0.0003290316,0.001183453,0.0007422218,0.001826504,0.0006173552,0.0002812011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7476566,"threshold_uncertainty_score":0.9995151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009388087520941106,"score_gpt":0.2035429575278906,"score_spread":0.1941548700069495,"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."}}