{"id":"W2888701353","doi":"10.1139/tcsme-2018-0066","title":"Burr edge occupancy: edge finishing index for milling machined parts","year":2018,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Enhanced Data Rates for GSM Evolution; Machining; Aerospace; Cutting tool; Mechanical engineering; Automotive industry; Sensitivity (control systems); Engineering drawing; Materials science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001856332,0.0001766169,0.0001937809,0.0000475711,0.0004299883,0.00003130865,0.0002428614,0.0001707184,0.00001436987],"category_scores_gemma":[0.00008002361,0.0001715682,0.0004000707,0.0002503582,0.00003080915,0.0001415683,0.00000491515,0.0002427009,5.208454e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002015595,"about_ca_system_score_gemma":0.00008037146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009946132,"about_ca_topic_score_gemma":0.008722529,"domain_scores_codex":[0.9990799,0.00000376528,0.0002557547,0.0001759528,0.00009293765,0.00039165],"domain_scores_gemma":[0.999347,0.0001242919,0.00004429658,0.0002212121,0.00009748971,0.0001657189],"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":[0.000008433855,0.000005705551,0.000005398971,0.0002400897,0.0001148433,3.892902e-8,0.0003559343,0.992975,0.0007655753,0.001182872,0.00018022,0.004165892],"study_design_scores_gemma":[0.0003999902,0.00004988263,0.00001355978,0.0000740353,0.00008770321,0.000001408904,0.00004058873,0.9821569,0.008706619,0.0005128825,0.007754786,0.0002016605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002067302,0.00015672,0.9957235,0.0001053584,0.001037468,0.0004162149,0.0002953158,0.000167182,0.00003096929],"genre_scores_gemma":[0.9299714,0.00003586798,0.06951893,0.00006170266,0.0001854556,0.00009914079,0.00001588989,0.00007148076,0.00004014625],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9279041,"threshold_uncertainty_score":0.6996346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01160910980873619,"score_gpt":0.222948453134954,"score_spread":0.2113393433262178,"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."}}