{"id":"W2301530155","doi":"10.2139/ssrn.1668633","title":"Scheduling of a Job Shop with Two Machine Centers Having Parallel Machines","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scheduling (production processes); Flow shop scheduling; Parallel computing; Job shop scheduling; Operations management; Engineering; Operating system; Schedule","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001801827,0.0008526987,0.002112475,0.0007638329,0.002268471,0.001535629,0.002192655,0.001862924,0.004020872],"category_scores_gemma":[0.001733088,0.001025955,0.00111702,0.0009513533,0.001416479,0.0009838027,0.001403488,0.0008349268,0.0003563537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001270291,"about_ca_system_score_gemma":0.001935133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005041885,"about_ca_topic_score_gemma":0.002846034,"domain_scores_codex":[0.9990913,0.000329277,0.00003949363,0.000171208,0.0001086312,0.0002601027],"domain_scores_gemma":[0.9982134,0.0007995174,0.0001767435,0.000150356,0.0001661684,0.0004938653],"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":[0.002407182,0.0005913604,0.001661959,0.0003139401,0.000134447,0.001619644,0.0001659577,0.9502134,0.01547432,0.01194257,0.001703195,0.013772],"study_design_scores_gemma":[0.0002044619,0.0004164627,0.000721567,0.000004939946,0.00003498414,0.0001217661,0.00006370312,0.9912484,0.002060085,0.004643481,0.0004556701,0.00002450069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7428952,0.000362287,0.2476388,0.0006036507,0.0002474471,0.000360525,0.0003026139,0.000502167,0.007087345],"genre_scores_gemma":[0.9416832,0.00008424046,0.05531275,0.00003034491,0.00007040911,0.00009358636,0.000131225,0.00004702336,0.002547337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005041885,"threshold_uncertainty_score":0.01345116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004345362079038653,"score_gpt":0.2168148239565853,"score_spread":0.2124694618775466,"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."}}