{"id":"W2804558154","doi":"10.5267/j.ijiec.2017.12.001","title":"Modelling and solving a bi-objective intermodal transport problem of agricultural products","year":2018,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Business; Agricultural engineering; Computer science; Environmental economics; Transport engineering; Engineering; Mathematical optimization; Economics; Mathematics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009074801,0.001420686,0.0010494,0.0008944558,0.0004727095,0.001768263,0.001215428,0.002069726,0.00267882],"category_scores_gemma":[0.001327334,0.0005380115,0.001167858,0.001253025,0.0005794179,0.001124287,0.0007974709,0.00108774,0.0002258386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001077494,"about_ca_system_score_gemma":0.001928436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01556932,"about_ca_topic_score_gemma":0.01224208,"domain_scores_codex":[0.9996221,0.0001651752,0.00001463959,0.00006503677,0.00005714134,0.00007583163],"domain_scores_gemma":[0.9994612,0.0003561566,0.00008001157,0.00001938377,0.00005346944,0.00002964876],"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":[0.00001151716,0.00001757086,0.0001640211,0.0000343002,0.00001206793,0.00003719383,0.00001252329,0.9961393,0.000224674,0.001686928,0.00007346583,0.001586446],"study_design_scores_gemma":[0.000005271662,0.00002664969,0.0001219509,0.000005349564,0.000009540086,0.000009644389,0.00002385869,0.9982783,0.0001250553,0.001120611,0.0002706705,0.000003148484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2269528,0.001175868,0.7568129,0.0004705559,0.0001036712,0.0002139701,0.0004056445,0.0001682762,0.01369628],"genre_scores_gemma":[0.869534,0.001080487,0.1202128,0.00007076861,0.00004629025,0.0004691192,0.0003827412,0.00005482136,0.008148978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01556932,"threshold_uncertainty_score":0.0309574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03235735448123322,"score_gpt":0.2136285733123037,"score_spread":0.1812712188310705,"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."}}