{"id":"W2034764259","doi":"10.1080/10940340008945698","title":"SIMULATION OF CHIP FORMATION IN ORTHOGONAL METAL CUTTING PROCESS: AN ALE FINITE ELEMENT APPROACH","year":2000,"lang":"en","type":"article","venue":"Machining Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Finite element method; Chip formation; Process (computing); Constitutive equation; Mechanical engineering; Machining; Lagrangian; Materials science; Cutting tool; Plane stress; Eulerian path; Applied mathematics; Structural engineering; Computer science; Engineering; Mathematics; Tool wear","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":[0.0003133812,0.0002473057,0.0003717733,0.000287068,0.0002069412,0.0004098453,0.0005103128,0.0007172357,0.00125852],"category_scores_gemma":[0.0005801124,0.0002195559,0.0003495885,0.0002172033,0.0005107881,0.0003716277,0.000455054,0.0002981395,0.0001525209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002640671,"about_ca_system_score_gemma":0.0004583516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00211041,"about_ca_topic_score_gemma":0.001326411,"domain_scores_codex":[0.9999064,0.00002322745,0.000004506559,0.00001153082,0.00003644199,0.00001784103],"domain_scores_gemma":[0.9997854,0.00009636569,0.00002930633,0.0000274287,0.00004567904,0.00001589365],"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":[0.00001808342,0.00001911174,0.0005324741,0.0000113297,0.00000410821,0.00003495967,0.00002029847,0.9926703,0.002540806,0.001672921,0.00004476487,0.002430863],"study_design_scores_gemma":[0.00000258179,0.000007456742,0.00005700728,8.615045e-7,8.944741e-7,0.000005163002,0.000003583859,0.999099,0.0005262632,0.0001875903,0.0001084249,0.000001109134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3161922,0.00008614711,0.6748341,0.00009686408,0.0000186389,0.00005325496,0.00009110531,0.0004251793,0.008202624],"genre_scores_gemma":[0.9359557,0.00007435988,0.06148934,0.00002186825,0.00000368457,0.00005611126,0.00007493194,0.0000345273,0.002289417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00211041,"threshold_uncertainty_score":0.004210174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008881703240282802,"score_gpt":0.2560429363889306,"score_spread":0.2471612331486478,"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."}}