{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005909484,0.0001903561,0.000210035,0.0001585747,0.0001141282,0.00005052932,0.000236312,0.00006253921,0.0000453453],"category_scores_gemma":[0.00003396117,0.0001553492,0.00008080059,0.000202397,0.00004079591,0.0001649867,0.00001675132,0.002118224,0.000005755516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001123733,"about_ca_system_score_gemma":0.0002573574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004306082,"about_ca_topic_score_gemma":0.0009053599,"domain_scores_codex":[0.9982332,0.00002113395,0.0002914893,0.0001336862,0.0002226547,0.001097841],"domain_scores_gemma":[0.9995325,0.00002926052,0.00008972024,0.000165579,0.00008198077,0.0001009425],"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":[0.00008527011,0.00005527549,0.0286351,0.00002930469,0.0003747206,0.000008788,0.000288981,0.9309424,0.00633688,0.01276286,0.000006091204,0.02047432],"study_design_scores_gemma":[0.002106106,0.0001424128,0.0005363416,0.00006523989,0.00006636287,0.0009164534,0.000430717,0.9916108,0.0005799878,0.003145006,0.00005065694,0.000349923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6286198,0.001256837,0.3687939,0.0001468769,0.0004037816,0.00007248946,0.00000245709,0.0001373518,0.0005664785],"genre_scores_gemma":[0.9195718,0.000543691,0.07944886,0.0000191749,0.000218246,0.0000029415,0.000004950516,0.00005448632,0.0001358061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.290952,"threshold_uncertainty_score":0.9202746,"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."}}