{"id":"W2799829979","doi":"10.1139/tcsme-2003-0012","title":"FINITE ELEMENT MODELING AND STABILITY ANALYSIS OF CHATTER IN END MILLING MACHINING","year":2003,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Finite element method; Timoshenko beam theory; Machining; Stability (learning theory); Structural engineering; Beam (structure); End milling; Point (geometry); Engineering; Mechanical engineering; Mathematics; Computer science; Geometry","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":[0.0002301531,0.0000937628,0.0001927598,0.00009540852,0.00006754442,0.000006711453,0.00006969048,0.00006844735,0.00001780032],"category_scores_gemma":[0.00003007189,0.00009321559,0.0002076837,0.0004498254,0.00001099596,0.00006399425,0.000002108389,0.0001434606,1.539113e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001291573,"about_ca_system_score_gemma":0.00002870794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001386234,"about_ca_topic_score_gemma":0.01284352,"domain_scores_codex":[0.9993785,0.000005357245,0.0002515387,0.0001102927,0.00007147325,0.0001828599],"domain_scores_gemma":[0.9996847,0.0000763699,0.00002258329,0.0001217574,0.0000280533,0.00006653425],"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":[0.000001074752,0.00000381284,0.00003170685,0.0001196734,0.0001621183,2.217798e-8,0.0005105933,0.9974566,0.0008027198,0.0005554264,1.343942e-7,0.0003561594],"study_design_scores_gemma":[0.0001564745,0.000008552664,0.00001073678,0.00002911163,0.0001802494,1.970006e-7,0.0001784534,0.9944279,0.004799838,0.0000945021,0.00002836223,0.00008568696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04371037,0.0001996732,0.9557828,0.0000201623,0.00007028916,0.0001283742,0.0000577287,0.00001890702,0.00001175572],"genre_scores_gemma":[0.955814,0.00005679956,0.04407239,0.00001358135,0.000003027363,0.00001719162,0.000004775348,0.00001695431,0.000001265379],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9121037,"threshold_uncertainty_score":0.7166987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204584532724453,"score_gpt":0.2080359325441187,"score_spread":0.1959900872168742,"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."}}