{"id":"W2002602643","doi":"10.1016/j.tre.2014.09.012","title":"A matheuristic for the liner shipping network design problem","year":2014,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Network planning and design; Transport engineering; Flow network; Computer science; Operations research; Business; Marine engineering; Engineering; Computer network; Mathematical optimization; Mathematics","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":[0.004245106,0.0002038978,0.0003356176,0.00006286164,0.0003645797,0.00006362658,0.000181299,0.00008985707,0.00005875505],"category_scores_gemma":[0.000199963,0.0001596132,0.00008787947,0.000521197,0.0001399957,0.00008281635,0.000001139036,0.0003142666,0.000007683471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001739705,"about_ca_system_score_gemma":0.00003801045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001393306,"about_ca_topic_score_gemma":0.00009396051,"domain_scores_codex":[0.9979139,0.0002506593,0.0007054187,0.0002883958,0.0003867057,0.0004549157],"domain_scores_gemma":[0.996973,0.002159701,0.00009031063,0.000252956,0.0003982389,0.0001257963],"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":[0.00001970087,0.0000185816,0.0003897542,0.004613271,0.00006223079,0.000002071263,0.0002022079,0.9285465,0.00001410673,0.04126374,0.004039269,0.02082855],"study_design_scores_gemma":[0.0009175668,0.0001828904,0.01014077,0.002876142,0.0004992708,0.000001325325,0.00004916159,0.7170097,0.00003820589,0.01140909,0.2563212,0.0005547315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00007487765,0.01288849,0.9839818,0.0007192583,0.0001249647,0.001836876,0.0000666268,0.0001760503,0.0001310138],"genre_scores_gemma":[0.2010743,0.1795582,0.6132953,0.0009560146,0.0006284685,0.002804426,0.001141879,0.0002211666,0.0003201749],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3706865,"threshold_uncertainty_score":0.6508839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1431290113692507,"score_gpt":0.3718995516219714,"score_spread":0.2287705402527206,"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."}}