{"id":"W4388698762","doi":"10.1139/tcsme-2023-0066","title":"On modelling the cutting forces and impact resistance of honed milling tools","year":2023,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Enhanced Data Rates for GSM Evolution; RADIUS; Materials science; Cracking; Mechanical engineering; Structural engineering; Engineering; Composite material; Computer science","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":[0.000160512,0.00009866514,0.0001254951,0.00003778951,0.0002035932,0.00001653099,0.0001293518,0.00006707455,0.000002104535],"category_scores_gemma":[0.00003441408,0.00007364475,0.000211799,0.0003290817,0.00001850116,0.00007993972,0.000003067656,0.0001510554,1.069832e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008463626,"about_ca_system_score_gemma":0.0000255566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005417581,"about_ca_topic_score_gemma":0.000986198,"domain_scores_codex":[0.9994482,0.00000288611,0.0001677319,0.00008989801,0.00008703755,0.0002042599],"domain_scores_gemma":[0.999501,0.000239938,0.00002918548,0.0001365022,0.00003252949,0.00006086849],"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":[0.000003223568,9.987225e-7,2.720809e-7,0.0001548323,0.000050579,2.671789e-8,0.0002852672,0.9958176,0.001474841,0.001699083,0.00001740823,0.0004958962],"study_design_scores_gemma":[0.0001162892,0.00001589438,0.000004366596,0.0001135019,0.00003107184,4.246513e-7,0.0001084681,0.9924819,0.006164646,0.0007764614,0.0001102388,0.00007671552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03507387,0.0001854403,0.9641105,0.0001087802,0.0001359661,0.0001948439,0.00008607218,0.00008542356,0.00001910602],"genre_scores_gemma":[0.9840913,0.0001444896,0.01565188,0.00001176143,0.00001528889,0.0000212967,0.000003770291,0.00003134253,0.00002886345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9490175,"threshold_uncertainty_score":0.3003146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01465229539951388,"score_gpt":0.2213481677228294,"score_spread":0.2066958723233155,"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."}}