{"id":"W2585027028","doi":"10.1155/2017/8608032","title":"Optimal Container Routing in Liner Shipping Networks Considering Repacking 20 ft Containers into 40 ft Containers","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Container (type theory); Transshipment (information security); Routing (electronic design automation); Computer science; Integer programming; Operations research; Mathematical optimization; Computer network; Engineering; Mathematics; Algorithm; Mechanical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006079466,0.0002714773,0.000542146,0.0001857338,0.0001842889,0.0001257347,0.0002181812,0.0001468023,0.00002618385],"category_scores_gemma":[0.0002265876,0.0002719362,0.0001541702,0.00008925699,0.00008299087,0.0008544929,0.000007313324,0.0006251655,5.794453e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001691842,"about_ca_system_score_gemma":0.00005520877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001138031,"about_ca_topic_score_gemma":0.001013828,"domain_scores_codex":[0.9979696,0.00002441189,0.001146658,0.0001966718,0.0002575544,0.000405139],"domain_scores_gemma":[0.9985695,0.0001376233,0.0006795455,0.0002440662,0.0002214429,0.000147755],"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":[0.0001689998,0.00001696451,0.02597461,0.00007387511,0.00006792409,0.0005932521,0.001339722,0.9616004,0.004199061,0.0005586437,0.00002217139,0.005384378],"study_design_scores_gemma":[0.0112319,0.000433776,0.3219232,0.003418067,0.000431201,0.0002315151,0.01067045,0.6393716,0.003107285,0.001105798,0.005989192,0.002085951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8345215,0.000591443,0.1620161,0.0002602699,0.00130271,0.0002488147,0.000006429965,0.0000874523,0.0009652214],"genre_scores_gemma":[0.9865783,0.0002335976,0.01263436,0.00006827214,0.0003667029,0.000005530407,0.00002910493,0.00005522148,0.00002888323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3222288,"threshold_uncertainty_score":0.9999733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215910978020971,"score_gpt":0.2533042709791305,"score_spread":0.2411451611989208,"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."}}