{"id":"W1971099568","doi":"10.1007/s10878-014-9825-y","title":"An improved two-machine flowshop scheduling with intermediate transportation","year":2015,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Job shop scheduling; Scheduling (production processes); Bin packing problem; Computer science; Theory of computation; Mathematical optimization; Bin; Approximation algorithm; Algorithm; Mathematics; 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":[0.0004263221,0.0001698391,0.0002596443,0.0002064985,0.00004280882,0.00009417065,0.0001668768,0.00008954787,0.00001724178],"category_scores_gemma":[0.00006716051,0.0001466027,0.00005235843,0.0003274215,0.00002383867,0.0008328895,0.000002718681,0.0002559408,0.00000165159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001049888,"about_ca_system_score_gemma":0.000110275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000515868,"about_ca_topic_score_gemma":0.000002187352,"domain_scores_codex":[0.9988342,0.00004872131,0.0005155152,0.0001076404,0.0003359552,0.0001579702],"domain_scores_gemma":[0.9986342,0.0000262396,0.000235112,0.0001381555,0.0007094003,0.0002569118],"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":[0.0002089607,0.00006959453,0.0001934966,0.00001012056,0.00004554095,0.000008531451,0.0005604157,0.9979947,0.0001613211,0.0001083822,0.00001478094,0.0006241596],"study_design_scores_gemma":[0.004540184,0.0005461711,0.00004185685,0.00004608429,0.0000672042,0.0000170238,0.0001988788,0.9932129,0.0009682896,0.0001504851,0.00002938253,0.0001815863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07547784,0.0001484425,0.9200141,0.0000416931,0.003956797,0.0001109841,0.000004494558,0.0001357249,0.0001099048],"genre_scores_gemma":[0.6477708,0.00003333189,0.3515896,0.00001945094,0.0004914986,0.000002383685,0.00004820318,0.00004168903,0.000003023521],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.572293,"threshold_uncertainty_score":0.5978284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008314866666477752,"score_gpt":0.2325324847667954,"score_spread":0.2242176181003176,"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."}}