{"id":"W2606334361","doi":"","title":"Combining Speed and Routing Decisions in Maritime Transportation","year":2014,"lang":"en","type":"article","venue":"","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"Routing (electronic design automation); Operations research; Computer science; Engineering; Computer network","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":[0.0001258693,0.00005297471,0.0000815061,0.00004007262,0.00001932966,0.00001880963,0.00002404572,0.00003365654,0.000100564],"category_scores_gemma":[0.00003845505,0.00005227489,0.000009323409,0.00004971655,0.00001013875,0.00004023865,0.000002812539,0.00006540387,0.000004556041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005970404,"about_ca_system_score_gemma":0.00000171683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001072073,"about_ca_topic_score_gemma":0.0003589815,"domain_scores_codex":[0.9996369,0.000005096581,0.0001424251,0.00006663039,0.00004577317,0.0001031789],"domain_scores_gemma":[0.9997971,0.0001011738,0.000007044594,0.00005369724,0.000007098241,0.00003385086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001245478,0.00006766658,0.3239934,0.00008682016,0.00002766276,0.00004782338,0.001657753,0.07553987,0.001549586,0.2402215,0.001623098,0.3551723],"study_design_scores_gemma":[0.0004129803,0.00001515413,0.3046063,0.00004074307,0.000007223545,0.000002509382,0.00008471602,0.6890675,0.0001371704,0.00277651,0.002691161,0.0001580038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6909676,0.00005031481,0.1509051,0.00007252723,0.0001635542,0.000107925,0.000005155629,0.0002592129,0.1574685],"genre_scores_gemma":[0.9966023,0.00002027661,0.003175307,0.00003372867,0.00001614234,7.897397e-7,0.00001363556,0.000009106922,0.0001287401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6135276,"threshold_uncertainty_score":0.2131708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01264942829090957,"score_gpt":0.2120431386954558,"score_spread":0.1993937104045463,"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."}}