{"id":"W2806289412","doi":"10.1016/j.cirp.2018.04.080","title":"Modelling and compensation of dominant thermally induced geometric errors using rotary axes’ power consumption","year":2018,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machine tool; Machining; Superposition principle; Invar; Position (finance); Ball screw; Power (physics); Power consumption; Control theory (sociology); Compensation (psychology); Thermal; Mechanical engineering; Computer science; Mathematics; Engineering; Thermal expansion; Materials science; Mathematical analysis; Physics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002391336,0.000660789,0.0003728998,0.0003920092,0.000200285,0.0006072781,0.0007269827,0.0005086595,0.001765699],"category_scores_gemma":[0.0009509437,0.0003585696,0.0004936235,0.0005262257,0.0002927849,0.000823312,0.0002564586,0.0003188134,0.0004629706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005165017,"about_ca_system_score_gemma":0.0006368139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007400989,"about_ca_topic_score_gemma":0.007432941,"domain_scores_codex":[0.9997699,0.0000347358,0.000009789632,0.0000484392,0.0001062115,0.00003094482],"domain_scores_gemma":[0.9997163,0.00008795565,0.00004078783,0.0000558299,0.00009144064,0.000007631184],"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":[0.00007485733,0.00001653925,0.001283183,0.00006221772,0.00001311449,0.00008390926,0.00006850813,0.9626662,0.0143427,0.002274342,0.0002854927,0.01882894],"study_design_scores_gemma":[0.000002731728,0.00002208263,0.001000062,0.00000501889,0.000008524678,0.00003554182,0.00001068782,0.9920034,0.005965166,0.0003300254,0.0006102253,0.000006602247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2733276,0.0004913626,0.7105765,0.0001333214,0.00007590436,0.00003763764,0.0002089418,0.00112302,0.01402559],"genre_scores_gemma":[0.9827659,0.0001266857,0.01380663,0.000007585057,0.000004986371,0.00001359051,0.00005151905,0.00008605712,0.003137005],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007400989,"threshold_uncertainty_score":0.01471585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1160838847928331,"score_gpt":0.3115415661362204,"score_spread":0.1954576813433873,"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."}}