{"id":"W2361742132","doi":"","title":"LOT SIZING WITH NON-ZERO SETUP TIMES FOR REWORK","year":2008,"lang":"en","type":"article","venue":"系统科学与系统工程学报(英文版)","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Rework; Sizing; Scheduling (production processes); Product (mathematics); Batch production; Production (economics); Computer science; Reliability engineering; Mathematical optimization; Engineering; Operations management; Mathematics; Economics","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":[0.0001073259,0.0002298923,0.0002429831,0.000102493,0.0001965889,0.000041265,0.0001731295,0.0001229257,0.0000993292],"category_scores_gemma":[0.00003862453,0.0002104768,0.00007475349,0.0003074302,0.00005114809,0.0001493271,0.00001918014,0.0001727102,0.0001194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004709866,"about_ca_system_score_gemma":0.00003552164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001439842,"about_ca_topic_score_gemma":0.000006931141,"domain_scores_codex":[0.9989408,0.000009331557,0.0002301754,0.0002503608,0.000187634,0.000381674],"domain_scores_gemma":[0.9993424,0.0001019151,0.00004057665,0.0003063634,0.00008415569,0.0001246087],"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":[0.0001355655,0.0001159709,0.002698975,0.0002452409,0.0003112372,0.00007928986,0.005112317,0.9367922,0.0005626632,0.0006355286,0.04283256,0.01047845],"study_design_scores_gemma":[0.003015408,0.0003012488,0.001471903,0.0002652406,0.00009556218,0.0001550362,0.0005272368,0.9514859,0.01108577,0.0003004972,0.03005283,0.001243322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1022066,0.001062845,0.8776935,0.0002659921,0.001005962,0.0006290358,0.00003625897,0.001686717,0.01541303],"genre_scores_gemma":[0.6239603,0.0001407277,0.3718783,0.000228974,0.0004095326,0.0000955626,0.00006259499,0.0001435858,0.003080493],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5217536,"threshold_uncertainty_score":0.8582996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01094142889652282,"score_gpt":0.2012722213406203,"score_spread":0.1903307924440975,"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."}}