{"id":"W2125276392","doi":"10.1007/s00170-009-2028-5","title":"A developed production control and scheduling model in the semiconductor manufacturing systems with hybrid make-to-stock/make-to-order products","year":2009,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Build to order; Scheduling (production processes); Workstation; Due date; Queue; Job shop; Computer science; Production control; Semiconductor device fabrication; Industrial engineering; Job shop scheduling; Flow shop scheduling; Idle; Production (economics); Engineering; Schedule; Operations management; Operating system","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":[0.0004838971,0.0002377726,0.0002795592,0.0006430061,0.00008885027,0.0001024092,0.0007536398,0.00007046778,0.0000010148],"category_scores_gemma":[0.0002164291,0.0001526688,0.00002646448,0.0002292002,0.00004474418,0.0001867546,0.00004767711,0.000597857,0.000002590449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001729541,"about_ca_system_score_gemma":0.00005502298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002875531,"about_ca_topic_score_gemma":0.000007944469,"domain_scores_codex":[0.9985231,0.00002869094,0.0004872071,0.0002549138,0.0004150085,0.0002911011],"domain_scores_gemma":[0.9991272,0.00005894507,0.0001862907,0.0002822285,0.0002883882,0.00005695826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001494043,0.00002199213,0.00001778864,0.00001171991,0.00006646589,0.00003276325,0.0003634912,0.9687542,0.009543056,0.00008474656,0.0000150143,0.02093932],"study_design_scores_gemma":[0.003559465,0.0004220954,0.001500718,0.0008369646,0.00008363018,0.005168963,0.002021253,0.2674868,0.7141917,0.002867478,0.001056933,0.0008040165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8977544,0.0002661486,0.08858647,0.0121234,0.000615422,0.000485183,0.000003626576,0.000137427,0.00002790074],"genre_scores_gemma":[0.8901052,0.00006597176,0.1091493,0.0003826434,0.0002040376,0.00002790567,0.000001533066,0.00002770254,0.00003566909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7046487,"threshold_uncertainty_score":0.6225653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01007463391586197,"score_gpt":0.2326971972156933,"score_spread":0.2226225632998313,"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."}}