{"id":"W2084285808","doi":"10.1115/1.1765147","title":"A New Principle of CNC Tool Path Planning for Three-Axis Sculptured Part Machining—A Steepest-Ascending Tool Path","year":2004,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Tool path; Tangent; Path (computing); Numerical control; Surface (topology); Machine tool; Computer science; Mathematics; Mechanical engineering; Engineering drawing; Algorithm; Geometry; Engineering","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":[0.0005615802,0.0005091718,0.0003182622,0.0008308027,0.0004705487,0.0006743119,0.000790245,0.000462162,0.001615507],"category_scores_gemma":[0.001148472,0.0003225346,0.0003767303,0.0007461254,0.001165477,0.0006308898,0.0006971768,0.001098789,0.0005820043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007295944,"about_ca_system_score_gemma":0.001440056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002393711,"about_ca_topic_score_gemma":0.002384895,"domain_scores_codex":[0.9993322,0.00006086301,0.00003113569,0.0001038519,0.0004440868,0.00002779426],"domain_scores_gemma":[0.9994324,0.0001151751,0.00005904168,0.0001105578,0.0002569084,0.00002584262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001564743,0.00005906779,0.001332231,0.0002908422,0.00003378466,0.000216678,0.000423962,0.1419163,0.095373,0.1715846,0.006385198,0.5822279],"study_design_scores_gemma":[0.00007845417,0.000358957,0.00204284,0.0000686282,0.00003988494,0.001076562,0.00006090719,0.8128844,0.06421346,0.04465844,0.07436921,0.0001482819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001919896,0.00008485252,0.9959027,0.00003978023,0.00002866695,0.00005289869,0.00001853725,0.0002223705,0.001730362],"genre_scores_gemma":[0.1207433,0.0003058688,0.8756506,0.00006747878,0.0000318915,0.0002000937,0.0001005642,0.00009810393,0.002802185],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002393711,"threshold_uncertainty_score":0.005404353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01090216592057106,"score_gpt":0.2467327790210101,"score_spread":0.235830613100439,"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."}}