{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00212708,0.001489126,0.0008074809,0.001957155,0.00141406,0.001987837,0.002523392,0.00104499,0.006130214],"category_scores_gemma":[0.007515288,0.0006561527,0.001332971,0.002180998,0.002327751,0.002923273,0.00295599,0.002224517,0.001191116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001339719,"about_ca_system_score_gemma":0.002014244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001268663,"about_ca_topic_score_gemma":0.00112196,"domain_scores_codex":[0.995477,0.001235388,0.0002015223,0.000723875,0.002000422,0.0003618338],"domain_scores_gemma":[0.9948608,0.002141559,0.0006228028,0.001270135,0.0009009799,0.0002037801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005262941,0.0004391254,0.00314268,0.0009948008,0.0001091106,0.0007913693,0.0009168932,0.1572058,0.03778434,0.2531883,0.0055824,0.539319],"study_design_scores_gemma":[0.0001108178,0.001208276,0.004619129,0.0003529978,0.0001577431,0.001568901,0.0007133425,0.4126267,0.0793271,0.4389924,0.0600347,0.0002880982],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01172367,0.0003131008,0.9762219,0.0003660707,0.0000942131,0.0001823177,0.00007277517,0.0008641247,0.01016196],"genre_scores_gemma":[0.3620284,0.0006426888,0.630739,0.0002543264,0.0001174612,0.000321224,0.0002759924,0.0003743517,0.005246494],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006130214,"threshold_uncertainty_score":0.02050763,"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."}}