{"id":"W2142187308","doi":"10.5539/ass.v6n7p108","title":"The Application of Setup Reduction in Lean Production","year":2010,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reduction (mathematics); Lean manufacturing; Production (economics); Computer science; Process management; Cost reduction; Manufacturing engineering; Industrial engineering; Risk analysis (engineering); Business; Engineering; Mathematics; Economics; Marketing; Microeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005161684,0.00004229039,0.00004349379,0.00005883927,0.0005052155,0.00004303193,0.0006908314,0.0000246112,3.414199e-7],"category_scores_gemma":[0.00004339777,0.00003501672,0.00001749366,0.00140596,0.000442525,0.000411754,0.00008038033,0.0001252355,0.000003287736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003665452,"about_ca_system_score_gemma":0.00008880925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001602368,"about_ca_topic_score_gemma":0.00002160713,"domain_scores_codex":[0.9992241,0.00000875239,0.0001425832,0.0002417641,0.0002486143,0.0001341448],"domain_scores_gemma":[0.9994826,0.00001427968,0.0001085066,0.00024462,0.0001266123,0.00002341609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[3.983437e-7,0.00001116918,0.00002064489,4.571737e-7,1.581678e-7,1.661658e-8,0.0002191879,0.000004982583,0.05173397,0.5722821,0.00002539229,0.3757015],"study_design_scores_gemma":[0.00007865841,0.000026173,0.05838085,0.000004088717,0.000001382246,0.00001364757,0.0002777189,0.005259084,0.06160511,0.8611942,0.01299988,0.0001591928],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03463826,0.000006369158,0.9264399,0.01190387,0.0004192496,0.0004830505,7.38618e-7,0.0001464242,0.0259621],"genre_scores_gemma":[0.9684011,0.000002304311,0.03139275,0.00001524835,0.00009486286,0.00005636988,5.308495e-7,0.000001952063,0.00003490773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9337628,"threshold_uncertainty_score":0.3885761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009154224838478142,"score_gpt":0.3084927764852967,"score_spread":0.2993385516468186,"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."}}