{"id":"W831360126","doi":"10.1177/0954405415590562","title":"Burr formation and correlation with cutting force and acoustic emission signals","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Acoustic emission; SIGNAL (programming language); Machining; Acoustics; Work (physics); Materials science; Mechanical engineering; Engineering; Computer science; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002812182,0.00014881,0.0002368206,0.0001169004,0.00003395114,0.00001858912,0.0001015213,0.00009936549,8.694599e-7],"category_scores_gemma":[0.0003008182,0.000103483,0.00003585459,0.0001565705,0.00002750867,0.0005875597,0.0000279068,0.0002647845,4.728535e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004637075,"about_ca_system_score_gemma":0.00002054076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.359374e-7,"about_ca_topic_score_gemma":9.257364e-8,"domain_scores_codex":[0.9991529,0.000002305483,0.0003919411,0.0000743424,0.0002611666,0.0001173319],"domain_scores_gemma":[0.9992856,0.00003847803,0.0002681534,0.00004084362,0.0002633017,0.0001035872],"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":[0.0000390573,0.000006500052,0.00001954105,0.0004127655,0.00002588234,3.461995e-7,0.0002447981,0.9762285,0.02147491,0.0009132655,0.00003815424,0.000596296],"study_design_scores_gemma":[0.0007395725,0.0001957249,0.00005975054,0.001003648,0.0001033587,0.000160335,0.0002377521,0.8274561,0.1692235,0.0004109036,0.0002564787,0.0001528172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3222716,0.0005338432,0.6766599,0.00005778947,0.0002457316,0.0001213613,0.000002420422,0.00004264917,0.00006474422],"genre_scores_gemma":[0.9892374,0.0001444046,0.01052627,0.000005659183,0.00005752197,0.000001729313,0.000001122032,0.00001703121,0.00000883861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6669658,"threshold_uncertainty_score":0.4219914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007593415260273871,"score_gpt":0.1939225040949486,"score_spread":0.1863290888346747,"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."}}