{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008475064,0.001031503,0.001948732,0.0008725401,0.00109516,0.0011735,0.002471367,0.001022564,0.00422682],"category_scores_gemma":[0.001095248,0.000470422,0.001312623,0.001281503,0.0004455583,0.001034782,0.001059016,0.001286807,0.0004612988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052247,"about_ca_system_score_gemma":0.002443032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006391364,"about_ca_topic_score_gemma":0.006261808,"domain_scores_codex":[0.9994161,0.0001507404,0.00002458122,0.0001346659,0.000138588,0.0001354282],"domain_scores_gemma":[0.9995334,0.0001453677,0.00003250017,0.00009758996,0.0001276303,0.0000635285],"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":[0.0007124246,0.0004304415,0.000516994,0.0002183777,0.00006680322,0.0002036879,0.00009408195,0.8805221,0.01393169,0.01068877,0.003433424,0.08918118],"study_design_scores_gemma":[0.00004166735,0.0000948364,0.000134052,0.000002976964,0.00001763363,0.00001792193,0.000007417747,0.9969177,0.0009257483,0.001265253,0.0005645712,0.00001023728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08225437,0.0002490506,0.9067028,0.000241421,0.000399808,0.0002076716,0.0001931753,0.001349921,0.00840175],"genre_scores_gemma":[0.655248,0.0001295567,0.3391117,0.00008267845,0.0001112962,0.0001963075,0.0002734345,0.0001269014,0.004720035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006391364,"threshold_uncertainty_score":0.01414019,"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."}}