{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001897022,0.001596281,0.001179595,0.001076543,0.0007927121,0.002155613,0.001220749,0.0017757,0.003449235],"category_scores_gemma":[0.004770008,0.001261528,0.001253026,0.002239105,0.001234724,0.004710228,0.00141209,0.001260065,0.0003411152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002020037,"about_ca_system_score_gemma":0.001099566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007202369,"about_ca_topic_score_gemma":0.006444062,"domain_scores_codex":[0.9985102,0.000816775,0.00004428892,0.0001969907,0.0002376944,0.0001940207],"domain_scores_gemma":[0.9977229,0.001695528,0.0002675201,0.00009214421,0.0001307367,0.00009122742],"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":[0.00001834567,0.00001618179,0.00025434,0.00002091093,0.00002374518,0.00001597154,0.00001388938,0.984791,0.0001649035,0.008564909,0.0002043052,0.005911577],"study_design_scores_gemma":[0.00001368031,0.00006852677,0.0002126,0.00001223154,0.00003809295,0.00002107333,0.00002034363,0.9676535,0.0002928027,0.02998157,0.00166829,0.00001727112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1566226,0.005476636,0.807975,0.001522282,0.0002969895,0.0001058921,0.0001749103,0.0002854425,0.02754021],"genre_scores_gemma":[0.9120838,0.003742707,0.07551016,0.0001506463,0.0003064063,0.00009340203,0.0001382281,0.0001653619,0.007809184],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007202369,"threshold_uncertainty_score":0.01465642,"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."}}