{"id":"W2011584411","doi":"10.1111/j.1753-0237.2009.00170.x","title":"Theoretical explanations for asymmetric relationships between gasoline and crude oil prices with focus on the US market","year":2009,"lang":"en","type":"article","venue":"OPEC Energy Review","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Energy Research Institute","funders":"","keywords":"Gasoline; Crude oil; Economics; Market power; Margin (machine learning); Focus (optics); Order (exchange); Econometrics; Financial economics; Microeconomics; Petroleum engineering; Chemistry; Monopoly; Computer science","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":[0.001591958,0.0001459468,0.000391318,0.0001030145,0.0002164628,0.00006308418,0.0001829654,0.00006305341,0.0003152378],"category_scores_gemma":[0.0005875272,0.0001001554,0.00007883227,0.0003780982,0.00006374124,0.00008316347,0.00002124641,0.0001400423,0.000004945116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003219217,"about_ca_system_score_gemma":0.00001403026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002135238,"about_ca_topic_score_gemma":0.0000299933,"domain_scores_codex":[0.9989405,0.00006905221,0.0004485227,0.0003106288,0.00004593508,0.0001853377],"domain_scores_gemma":[0.9985114,0.0007865478,0.0002307528,0.000353941,0.00003984098,0.00007753094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001159788,0.0000305643,0.007676566,0.00007538465,0.00002412173,3.169371e-7,0.000005616247,0.000001149409,2.31642e-8,0.9581776,0.001044451,0.0329526],"study_design_scores_gemma":[0.0005699245,0.0003200523,0.1106772,0.000738591,0.00009691496,0.000006351045,0.000006510507,0.01099728,0.000002279862,0.3576125,0.5185166,0.0004558168],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01073698,0.12454,0.02228311,0.04817547,0.00010239,0.0007623677,0.000560635,0.00006016854,0.7927788],"genre_scores_gemma":[0.9408171,0.05482784,0.001819809,0.001123291,0.00009221331,0.000111288,0.000054327,0.00001772204,0.001136392],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9300801,"threshold_uncertainty_score":0.4084219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03386938122534583,"score_gpt":0.2383012838428178,"score_spread":0.204431902617472,"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."}}