{"id":"W2202754608","doi":"10.1007/s12541-015-0261-4","title":"Study on a novel thermal error compensation system for high-precision ball screw feed drive (1st report: Model, calculation and simulation)","year":2015,"lang":"en","type":"article","venue":"International Journal of Precision Engineering and Manufacturing","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Ball screw; Compensation (psychology); Thermal; Control theory (sociology); Ball (mathematics); Machine tool; Correctness; Feed forward; Computer science; Mechanical engineering; Engineering; Control engineering; Algorithm; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003069786,0.0004226044,0.0005270882,0.0002700851,0.0006075838,0.0005039272,0.0007078844,0.0005433655,0.002620373],"category_scores_gemma":[0.0004108435,0.0002793038,0.0004803537,0.0003077569,0.0002384142,0.0009484902,0.0001837436,0.0002159175,0.0002506729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005402651,"about_ca_system_score_gemma":0.0007307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006025808,"about_ca_topic_score_gemma":0.004863661,"domain_scores_codex":[0.9997295,0.00003564022,0.00001029961,0.00005852049,0.0001420284,0.00002409789],"domain_scores_gemma":[0.9997448,0.00007087798,0.0000282965,0.00002601077,0.0001199894,0.000009979133],"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":[0.001192484,0.0005204214,0.00802499,0.001341021,0.0002539722,0.0005160177,0.0004753481,0.5783365,0.2644947,0.004690676,0.002714318,0.1374395],"study_design_scores_gemma":[0.00007801804,0.0008746473,0.005643713,0.00001637404,0.0001454865,0.000190316,0.00007587781,0.9423033,0.0475997,0.0002771121,0.002757919,0.00003766971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5949598,0.001419441,0.3901507,0.0002700628,0.0001847958,0.0002168908,0.0001564013,0.001764358,0.0108776],"genre_scores_gemma":[0.9827754,0.0001773621,0.01462559,0.00001591785,0.00001246495,0.00003878026,0.00004641137,0.00002069902,0.002287431],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006025808,"threshold_uncertainty_score":0.01198149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04417110265541878,"score_gpt":0.2974561159138358,"score_spread":0.253285013258417,"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."}}