{"id":"W1979595082","doi":"10.1007/s00170-014-6714-6","title":"Calibration of the cutting process and compensation of the compliance error by using on-machine probing","year":2014,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Offset (computer science); Compensation (psychology); Machine tool; Calibration; Process (computing); End milling; Tool path; Coordinate-measuring machine; Mechanical engineering; Engineering; Computer science; Machining; Mathematics","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":[0.0002560855,0.00009870419,0.0001618022,0.0001079026,0.00006721652,0.000006064748,0.0005761527,0.00005707286,0.000001523857],"category_scores_gemma":[0.0001385908,0.00005547566,0.00004446032,0.00008150467,0.0001578107,0.0001236432,0.00007482131,0.0003090904,3.84169e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005871442,"about_ca_system_score_gemma":0.00001064335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001877105,"about_ca_topic_score_gemma":0.000003151574,"domain_scores_codex":[0.999218,0.00002880486,0.0003446936,0.00007201733,0.00024197,0.00009448783],"domain_scores_gemma":[0.9991268,0.00007885908,0.0004983418,0.0001590552,0.00012693,0.00001000689],"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":[0.00007161105,0.00002982754,0.002254795,0.00005829806,0.00009241921,3.651629e-7,0.0001801791,0.2157994,0.7597136,0.00130725,0.00001960756,0.02047265],"study_design_scores_gemma":[0.0002981322,0.00004666208,0.000604347,0.0002859452,0.00001650743,0.00003577573,0.00006912158,0.01446817,0.9744307,0.009531813,0.0001605181,0.00005228921],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9544761,0.0001476432,0.04382941,0.0009844077,0.0003136872,0.0001416126,0.000003227917,0.00003921907,0.00006466186],"genre_scores_gemma":[0.9967751,0.00002917726,0.003090016,0.00005621135,0.00002876881,0.000002939832,4.30322e-7,0.00001225256,0.000005120241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2147171,"threshold_uncertainty_score":0.2262232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01646974815670949,"score_gpt":0.2672953370618877,"score_spread":0.2508255889051782,"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."}}