{"id":"W2586095345","doi":"10.3390/machines5010005","title":"A Method for Design of Modular Reconfigurable Machine Tools","year":2017,"lang":"en","type":"article","venue":"Machines","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Modular design; Control reconfiguration; Construct (python library); Computer science; Identification (biology); Software; Set (abstract data type); Engineering drawing; Machine tool; Machining; Engineering; Embedded system; Programming language; Mechanical 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":[0.000203449,0.00009236384,0.000155648,0.00003521287,0.0001106001,0.00007043168,0.0001866922,0.0000419292,0.00006351992],"category_scores_gemma":[0.00008620365,0.00007976,0.00003877811,0.00001394651,0.000009436986,0.0001554015,0.000009999693,0.0000407071,0.000001812687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000647064,"about_ca_system_score_gemma":0.000004531675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005962322,"about_ca_topic_score_gemma":0.000006258662,"domain_scores_codex":[0.9996074,0.000009824128,0.0001311539,0.00009529677,0.00004859667,0.0001076922],"domain_scores_gemma":[0.9995729,0.00006171915,0.00005834809,0.0002525715,0.00003113941,0.00002326282],"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":[0.00001722174,0.000007388103,0.00008876039,0.0002435196,0.0000272538,3.424844e-7,0.00005481294,0.8791281,0.004046389,0.0002693352,0.000180444,0.1159364],"study_design_scores_gemma":[0.0002561933,0.00002112075,0.0006995453,0.00001881255,0.00001460861,0.000001118757,0.000001199865,0.9462885,0.04849575,0.001962451,0.002143063,0.00009766699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002090001,0.0002437189,0.9941479,0.00006342496,0.0001457982,0.0002160273,0.00002907267,0.00008489157,0.002979166],"genre_scores_gemma":[0.5383663,0.00007113491,0.4606585,0.00001675869,0.00006757311,0.00006122831,0.00001843015,0.00003660878,0.0007035128],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5362763,"threshold_uncertainty_score":0.3252518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03596449582365892,"score_gpt":0.2788526031616607,"score_spread":0.2428881073380018,"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."}}