{"id":"W1975356408","doi":"10.1016/s0890-6955(02)00234-1","title":"Optimized feed scheduling in three axes machining","year":2002,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Scheduling (production processes); Machine tool; Ball screw; Gain scheduling; Engineering; Control theory (sociology); Tool path; Control engineering; Computer science; Mechanical engineering; Control system; Control (management); Operations management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004353211,0.0006516063,0.0009554637,0.0004102935,0.0004346065,0.0007667135,0.0007086391,0.0005881197,0.002225371],"category_scores_gemma":[0.0009236469,0.0005170827,0.0003675251,0.0008193568,0.0004462035,0.0004627966,0.0003791161,0.0005503986,0.0002320689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006296835,"about_ca_system_score_gemma":0.0009920072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005078365,"about_ca_topic_score_gemma":0.004981383,"domain_scores_codex":[0.9997897,0.00006437874,0.000008962803,0.00002915355,0.00005621719,0.00005168333],"domain_scores_gemma":[0.99958,0.000225389,0.00006226606,0.00002683219,0.00006845897,0.00003700658],"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":[0.0004790869,0.00008414774,0.0002981064,0.00007135208,0.00001692541,0.00004695051,0.00004139119,0.9562473,0.006472273,0.003677475,0.0006121724,0.03195282],"study_design_scores_gemma":[0.00003502886,0.0001165752,0.0003041487,0.000003331719,0.00000630859,0.000009677273,0.00001301698,0.9951825,0.001970283,0.002029869,0.0003227701,0.000006551237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3283581,0.000812465,0.6613575,0.0001836382,0.0001438071,0.000118972,0.0001984014,0.0005784087,0.008248684],"genre_scores_gemma":[0.8982742,0.0002107306,0.09908181,0.00002805273,0.00001911431,0.00006349538,0.0001149005,0.0001052856,0.002102302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005078365,"threshold_uncertainty_score":0.01009762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01306918380288548,"score_gpt":0.2378326859678843,"score_spread":0.2247635021649988,"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."}}