{"id":"W1991234588","doi":"10.1115/dscc2010-4039","title":"Tracking Control of Flexible Ball Screw Drives With Runout Effect Compensation","year":2010,"lang":"en","type":"article","venue":"","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ball screw; Control theory (sociology); Ball (mathematics); Machining; Machine tool; Tracking error; Computer science; Control engineering; Tracking (education); Engineering; Mechanical engineering; Artificial intelligence; Mathematics; Control (management)","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":[0.000250826,0.0001402772,0.00027577,0.00007795428,0.00003633079,0.00004578047,0.00008919555,0.00006537882,0.000149405],"category_scores_gemma":[0.00003074526,0.0001046133,0.00004340327,0.00008797001,0.00003577857,0.0001533112,0.000004550705,0.0002226639,0.00004141654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001403155,"about_ca_system_score_gemma":0.000008059355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003737423,"about_ca_topic_score_gemma":0.00005818126,"domain_scores_codex":[0.99931,0.00005824342,0.0001898966,0.0001181726,0.0001476428,0.0001760271],"domain_scores_gemma":[0.9994506,0.0002071656,0.00005004395,0.0001756719,0.00007440541,0.00004208919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009874408,0.0000213691,0.084126,0.000170855,0.000244378,0.000005743385,0.001161864,0.03717873,0.8616345,0.009490967,0.00008813188,0.005778711],"study_design_scores_gemma":[0.009443787,0.001030101,0.2168302,0.0003548152,0.0001412778,0.00004735294,0.0001620639,0.5932071,0.1731823,0.0000389758,0.004739482,0.0008225029],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.822815,0.00008014957,0.153257,0.0000284543,0.0003406281,0.0004453023,0.000002671003,0.0004038766,0.02262686],"genre_scores_gemma":[0.9987232,2.850185e-7,0.0007394472,0.00001351034,0.0001027755,0.00002251241,0.000004023091,0.00003029751,0.0003639174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6884522,"threshold_uncertainty_score":0.4266005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003296461131668663,"score_gpt":0.1975661375335601,"score_spread":0.1942696764018914,"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."}}