{"id":"W3113179601","doi":"","title":"Correlations and Volatility Spillovers between the Carbon Trading Price and Bunker Index for the Maritime Industry","year":2016,"lang":"en","type":"article","venue":"Review of Economics and Finance","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bunker; Volatility (finance); Greenhouse gas; Index (typography); Economics; Natural resource economics; Industrial organization; Environmental economics; Econometrics; Computer science; Coal; Waste management; Ecology; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003777508,0.00006372622,0.0001360401,0.000004669577,0.0001178559,0.000007090048,0.00007154806,0.0000474562,0.00007544561],"category_scores_gemma":[0.00002241543,0.00003274932,0.00002311601,0.0000368467,0.0002160929,0.00006170214,0.00003610827,0.00006527163,4.011691e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001409219,"about_ca_system_score_gemma":0.000008083242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005556349,"about_ca_topic_score_gemma":0.00001105358,"domain_scores_codex":[0.9995515,0.000008581369,0.0001816702,0.000147012,0.00002023699,0.00009098214],"domain_scores_gemma":[0.9995383,0.0002147116,0.00008821419,0.0001306005,0.000003363588,0.00002480382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005352515,0.00001249469,0.7311589,0.0002346879,0.00001044495,9.267256e-8,0.00005695186,0.00001691112,0.000009357769,0.001595664,0.0002644859,0.2666346],"study_design_scores_gemma":[0.0001798719,0.00002439115,0.8760654,0.0004496661,0.00003696641,0.000002432816,0.000006716682,0.01506228,0.000006181881,0.000745377,0.1073306,0.00009013517],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809051,0.01313206,0.0003771966,0.00284836,0.0000249511,0.0004182944,0.00004791173,0.000002188839,0.002243978],"genre_scores_gemma":[0.9176379,0.08195315,0.00008745182,0.0001002679,0.00001460616,0.00001098232,6.797031e-7,0.000003298463,0.0001916071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2665445,"threshold_uncertainty_score":0.1335479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01303569623530923,"score_gpt":0.2138346282959743,"score_spread":0.200798932060665,"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."}}