{"id":"W2991053346","doi":"10.1016/b978-0-12-409548-9.09270-8","title":"Marine Transportation and Energy Use","year":2019,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Greenhouse gas; Marine transportation; Energy sector; Energy consumption; Climate change; Business; Energy (signal processing); Consumption (sociology); Marine energy; Natural resource economics; Environmental economics; Environmental science; Engineering; Transport engineering; Economics; Oceanography","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007673576,0.0002868827,0.0002778961,0.00004343757,0.00008083338,0.00002822434,0.0001351889,0.000223323,0.01283625],"category_scores_gemma":[0.000001594528,0.0002576926,0.00009923091,0.00001022192,0.0001572652,0.0000760883,0.00004096978,0.0001836879,0.0002132519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004197523,"about_ca_system_score_gemma":0.00001911615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004364662,"about_ca_topic_score_gemma":0.0004639373,"domain_scores_codex":[0.9987635,0.000006564012,0.0002877103,0.0004590844,0.0002736152,0.0002095114],"domain_scores_gemma":[0.9993894,0.0000269083,0.0001009539,0.0003327149,0.000007111949,0.0001429335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001006611,0.000007463712,0.001447348,0.00002328582,0.00001120779,0.00002451074,0.00005582683,0.000009884645,0.0000500215,0.004700541,0.0001803484,0.9934795],"study_design_scores_gemma":[0.0001446173,0.00003918279,0.006913961,0.00006409092,0.00005856835,0.000005165052,0.000001128467,0.00003349684,0.00001084024,0.001752331,0.9906555,0.0003210896],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001084992,0.00006470956,0.00001419829,0.00002319416,0.00009364362,0.0001256798,0.00003884658,0.00003667285,0.998518],"genre_scores_gemma":[0.003343386,0.0002068761,0.0004730915,0.0002165558,0.0000309051,0.000006045033,0.0001141203,0.00004812197,0.9955609],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9931584,"threshold_uncertainty_score":0.9999875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008069272927351297,"score_gpt":0.1857929086814412,"score_spread":0.1777236357540899,"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."}}