{"id":"W4220888534","doi":"10.1007/s00170-022-09074-7","title":"Correlation assessment and modeling of intra-axis errors of prismatic axes for CNC machine tools","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure","funders":"","keywords":"Machine tool; Numerical control; Repeatability; Parametric statistics; Algorithm; Context (archaeology); Computer science; Parametric model; Engineering; Mathematics; Machining; Mechanical engineering; Statistics","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":[0.002861843,0.000766925,0.0004284573,0.001393597,0.0004823527,0.0009258761,0.0008583599,0.0006450188,0.0009393101],"category_scores_gemma":[0.009121344,0.0003929486,0.0007128076,0.001759259,0.0003555345,0.0007105641,0.0005510563,0.0004872706,0.0004193812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007827693,"about_ca_system_score_gemma":0.001597941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0101274,"about_ca_topic_score_gemma":0.01070845,"domain_scores_codex":[0.9978439,0.0005360957,0.0001157785,0.0004507727,0.0009360264,0.0001175019],"domain_scores_gemma":[0.9931977,0.002678503,0.0008945284,0.0009673644,0.002189814,0.0000722187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007306014,0.0001709673,0.06362417,0.0002268298,0.0001594276,0.0001940448,0.000388363,0.7715155,0.02234491,0.002702992,0.001219624,0.1367226],"study_design_scores_gemma":[0.000009441545,0.0001172988,0.0216473,0.00001827156,0.00003858024,0.0001084503,0.00004230507,0.9652436,0.01173752,0.0003215309,0.0006885799,0.00002715875],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4075159,0.0006008772,0.5866925,0.00007691888,0.00005843153,0.00008102456,0.0003998501,0.001659812,0.002914703],"genre_scores_gemma":[0.9581094,0.0001128033,0.04050537,0.00001070067,0.000009027644,0.00003160184,0.000290866,0.0001502508,0.0007800021],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0101274,"threshold_uncertainty_score":0.02013689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02103506439932296,"score_gpt":0.2831980256639611,"score_spread":0.2621629612646381,"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."}}