{"id":"W2108138788","doi":"10.1109/icma.2005.1626684","title":"Robust adaptive control of machining operations","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Machining; Numerical control; Robustness (evolution); Parametric statistics; Machine tool; Control theory (sociology); Adaptive control; Noise (video); Cutting tool; Computer science; Process (computing); Engineering; Control engineering; Mechanical engineering; Control (management); Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006477574,0.0009674752,0.0006520346,0.0002884895,0.0002680061,0.0009028405,0.000878794,0.0005802634,0.001222098],"category_scores_gemma":[0.002500864,0.0002410932,0.0003060151,0.0003367238,0.0006351101,0.000390053,0.0004708836,0.0008887106,0.0002690248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004934396,"about_ca_system_score_gemma":0.000470973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00378593,"about_ca_topic_score_gemma":0.001957716,"domain_scores_codex":[0.9993883,0.0001203767,0.00003776112,0.0001850327,0.0002071347,0.00006129644],"domain_scores_gemma":[0.9992566,0.0003605236,0.0001402284,0.00005908209,0.0001620648,0.00002151042],"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":[0.0001484713,0.00005182753,0.0002601236,0.0001530846,0.00004707902,0.00007162226,0.00007053823,0.8994831,0.01332581,0.007774449,0.0008005498,0.07781339],"study_design_scores_gemma":[0.00001811625,0.00006752561,0.0002148675,0.000004392607,0.000005316708,0.000009327679,0.000003884827,0.9965527,0.001137621,0.001400513,0.0005799367,0.000005789202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01775075,0.0004628504,0.976418,0.00009817437,0.0000925124,0.00004627948,0.00003004827,0.0007383357,0.004363091],"genre_scores_gemma":[0.968955,0.0003776336,0.02772356,0.00005408054,0.00007803656,0.0001316741,0.00005964117,0.00003113228,0.002589131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00378593,"threshold_uncertainty_score":0.007527828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009025337983348388,"score_gpt":0.1943538539476884,"score_spread":0.1853285159643401,"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."}}