{"id":"W7014241079","doi":"","title":"Obtaining optimal and approximate solutions to the problem of scheduling inbound and outbound trucks in cross docking operations","year":2009,"lang":"en","type":"article","venue":"Borås Academic Digital Archive (University of Borås)","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Wilfrid Laurier University","keywords":"Truck; Heuristic; Scheduling (production processes); Job shop scheduling; Mathematical model; Integer programming; Vehicle routing problem","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004005879,0.0001352859,0.0002227556,0.0002153304,0.0002422201,0.00008164446,0.0002220437,0.00008396188,0.000001945758],"category_scores_gemma":[0.00007622127,0.0001494251,0.00003657029,0.0003170385,0.0002187935,0.0006697779,0.0001786844,0.000365156,7.673659e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000361243,"about_ca_system_score_gemma":0.00003742774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003278851,"about_ca_topic_score_gemma":0.00003120637,"domain_scores_codex":[0.9990918,0.00004218927,0.0002439661,0.0002171367,0.0001342955,0.0002705838],"domain_scores_gemma":[0.9995302,0.0001428211,0.0000613805,0.0001260174,0.00004357942,0.00009598634],"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":[0.00002241454,0.00001424881,0.003763935,0.00003815088,0.00002208624,0.000002027263,0.008316471,0.9626527,0.001699051,0.006117887,0.00001071873,0.01734035],"study_design_scores_gemma":[0.0006311695,0.00007057208,0.04227609,0.0002156977,0.0000215575,0.00001592926,0.003805432,0.9496452,0.00007364791,0.002664284,0.0003400269,0.0002404144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6495936,0.0001106431,0.3485222,0.0003059289,0.00001097371,0.0002080367,0.00006572497,0.00004772736,0.001135229],"genre_scores_gemma":[0.8767039,0.00007447059,0.1231394,0.00002061072,0.00001402356,6.523113e-7,0.00001235942,0.00001108066,0.00002349818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2271104,"threshold_uncertainty_score":0.609338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01645139821972165,"score_gpt":0.2444850269484162,"score_spread":0.2280336287286945,"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."}}