{"id":"W2304897825","doi":"10.1080/16864360.2015.1114394","title":"5D Cubic B-Spline Interpolated Compensation of Geometry-Based Errors in Five-Axis Surface Machining","year":2015,"lang":"en","type":"article","venue":"Computer-Aided Design and Applications","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Monotone cubic interpolation; Geometry; Machining; Surface (topology); B-spline; Compensation (psychology); Spline interpolation; Mathematics; Materials science; Bicubic interpolation; Computer science; Engineering; Mathematical analysis; Computer vision; Mechanical engineering","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":[0.000810346,0.0003570285,0.000432917,0.0006354483,0.0002103385,0.0004662546,0.0007094334,0.0005671459,0.001533762],"category_scores_gemma":[0.002012882,0.000249213,0.0004050773,0.0007571241,0.0002700563,0.0004747373,0.0004800114,0.0005300311,0.0003119944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002940155,"about_ca_system_score_gemma":0.000664045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003817173,"about_ca_topic_score_gemma":0.005089476,"domain_scores_codex":[0.9995116,0.0001030501,0.00002601768,0.00005337055,0.0002707587,0.00003530648],"domain_scores_gemma":[0.9992587,0.0002382501,0.00007800668,0.0001195244,0.0002759109,0.00002956316],"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":[0.0007206943,0.0001450682,0.00418619,0.0003207206,0.00004687552,0.0001530743,0.0002862805,0.5325917,0.03735816,0.005508941,0.00195261,0.4167297],"study_design_scores_gemma":[0.000006642138,0.0000700177,0.001243428,0.00001056869,0.000006445324,0.00003856389,0.00002140755,0.9918949,0.005234079,0.0003594032,0.001101871,0.0000125974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1891874,0.0005904451,0.8060949,0.00009122724,0.0001763535,0.00003790046,0.00008739685,0.0008556911,0.002878669],"genre_scores_gemma":[0.8452932,0.0002135998,0.152132,0.00001645268,0.00001289158,0.00002197794,0.0001669414,0.0001196154,0.002023268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003817173,"threshold_uncertainty_score":0.007589877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03049662811463709,"score_gpt":0.2671972755194065,"score_spread":0.2367006474047694,"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."}}