{"id":"W4200285175","doi":"10.3390/jrfm14120620","title":"The Skewness Risk in the Energy Market","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Skewness; Predictability; Stock market; Econometrics; Financial economics; Economics; Statistics; Mathematics; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009643569,0.0003244142,0.0004219498,0.0008773792,0.0002335149,0.001375643,0.0002587368,0.0004088608,0.001317255],"category_scores_gemma":[0.005477103,0.0001557089,0.000416918,0.0005830058,0.0007660354,0.002299236,0.0006422868,0.0005571686,0.0001598866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002921322,"about_ca_system_score_gemma":0.0003413779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008068075,"about_ca_topic_score_gemma":0.0003450275,"domain_scores_codex":[0.9996917,0.00008706228,0.00002252119,0.00004304453,0.0001026981,0.00005295229],"domain_scores_gemma":[0.9976432,0.001035253,0.000861795,0.00009748514,0.0002250111,0.0001373394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000396684,0.000155587,0.1887788,0.0002683776,0.0004148106,0.003649439,0.0007544046,0.2791955,0.01917088,0.4407508,0.002968341,0.06349628],"study_design_scores_gemma":[0.00002849534,0.0001933432,0.07725292,0.00008395229,0.00009659302,0.001624146,0.0003806024,0.5894386,0.002900351,0.3253114,0.002580841,0.0001086497],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9050105,0.003920506,0.08084074,0.001067642,0.00009140005,0.0000259224,0.000138011,0.0001221677,0.008783229],"genre_scores_gemma":[0.9978296,0.0006449411,0.00087108,0.00001943986,0.00006326074,0.000005522687,0.00003641156,0.000007592675,0.0005220366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001375643,"threshold_uncertainty_score":0.005100071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007361485205245006,"score_gpt":0.1871836271987604,"score_spread":0.1798221419935154,"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."}}