{"id":"W4379046899","doi":"10.1016/j.cirpj.2023.05.004","title":"Identification and effect of chip shear band on chatter vibration in the turning of Nickel Alloy 718","year":2023,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adiabatic shear band; Chip formation; Machining; Vibration; Materials science; Chip; Shear (geology); Alloy; Natural frequency; Structural engineering; Metallurgy; Acoustics; Tool wear; Engineering; Composite material; Physics; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007672391,0.00005215065,0.0001110384,0.00050407,0.00005295891,0.00001788858,0.0001416829,0.00004125918,6.701251e-7],"category_scores_gemma":[0.0001362634,0.00003592976,0.000009319052,0.0003595752,0.0001509163,0.000207877,0.00001592657,0.0001428013,3.150474e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001011914,"about_ca_system_score_gemma":0.000008723855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.228118e-7,"about_ca_topic_score_gemma":6.378393e-7,"domain_scores_codex":[0.9994901,0.0000104642,0.0001909602,0.00007376748,0.0001450923,0.00008963823],"domain_scores_gemma":[0.9996827,0.00007682046,0.0001180795,0.00007603256,0.00003505621,0.0000113129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005817876,0.0000234356,0.008552632,0.0005498292,0.00002200649,0.0000116176,0.002119333,0.3747267,0.4997754,0.0004806857,0.00003753745,0.1136427],"study_design_scores_gemma":[0.0003061384,0.000236916,0.04120139,0.000137329,0.000009334611,0.00003622583,0.0002189887,0.01171704,0.9452667,0.000788418,0.000026738,0.00005473343],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982235,0.0001258985,0.001188433,0.0003029895,0.00006459909,0.00005339875,3.796256e-7,0.00001621926,0.00002459731],"genre_scores_gemma":[0.999623,0.0002290437,0.0001231305,0.000008082687,0.000009255485,0.000001431161,2.786311e-7,0.000003845097,0.000001913467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4454914,"threshold_uncertainty_score":0.1465173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005418850092307134,"score_gpt":0.234357422280698,"score_spread":0.2289385721883909,"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."}}