{"id":"W897097795","doi":"10.1007/s00170-015-7532-1","title":"The edge–torus tangency problem in multipoint machining of triangulated surface models","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"University of Waterloo","keywords":"Torus; Tangent; Surface (topology); Enhanced Data Rates for GSM Evolution; Tensor product; Geometry; Triangulation; Pyramid (geometry); Toroid; Mathematics; Computer science; Pure mathematics; 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":[0.0006490902,0.0003851351,0.0008932018,0.0009123086,0.000957065,0.001442327,0.001237078,0.001770689,0.0044835],"category_scores_gemma":[0.004105562,0.000655931,0.0006067441,0.0007345169,0.001511768,0.001979301,0.001948398,0.00116757,0.0002332201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008113419,"about_ca_system_score_gemma":0.0005843708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002831937,"about_ca_topic_score_gemma":0.002734805,"domain_scores_codex":[0.9995994,0.0001244039,0.00002408887,0.00008843003,0.0001213895,0.00004231],"domain_scores_gemma":[0.9986283,0.0008394505,0.0002010688,0.0001319255,0.0000990919,0.0001002994],"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":[0.000173739,0.00006006482,0.001762466,0.0002281286,0.00004900483,0.0005946129,0.0003362685,0.6642094,0.002492946,0.2906848,0.001934715,0.03747384],"study_design_scores_gemma":[0.00001835403,0.0000498502,0.0004694917,0.00003491874,0.00001126363,0.0001436342,0.00009804172,0.8518867,0.0009396606,0.1441865,0.002146106,0.00001548415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4604303,0.001064268,0.5175714,0.0007336579,0.0001326788,0.00009874239,0.0002045872,0.0002523336,0.0195121],"genre_scores_gemma":[0.9300081,0.0003293776,0.06240392,0.00004887216,0.00003517874,0.0000469106,0.0002120255,0.000136539,0.006779164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0044835,"threshold_uncertainty_score":0.01499879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01398483644113618,"score_gpt":0.2570967278077283,"score_spread":0.2431118913665921,"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."}}