{"id":"W3130454904","doi":"10.5267/j.ac.2021.2.007","title":"On the price volatility of steel futures and its influencing factors in China","year":2021,"lang":"en","type":"article","venue":"Accounting","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Futures contract; Volatility (finance); Economics; Autoregressive conditional heteroskedasticity; Financial economics; Monetary economics; Econometrics","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":[0.000968672,0.0002701794,0.0003017584,0.001145336,0.0003966362,0.0007983745,0.0003574627,0.0002937171,0.0007810784],"category_scores_gemma":[0.002028787,0.0002088446,0.0006699216,0.001421833,0.0002661795,0.0006872785,0.0003680217,0.0003287685,0.00005628106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009595201,"about_ca_system_score_gemma":0.0008053266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04147691,"about_ca_topic_score_gemma":0.03036413,"domain_scores_codex":[0.9997024,0.00004535301,0.0000220339,0.00006828327,0.00009939347,0.0000625532],"domain_scores_gemma":[0.9988475,0.0004857158,0.0003311141,0.00006586362,0.000182988,0.00008678524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001045498,0.00005382901,0.9293506,0.00005835521,0.0002434228,0.0008708693,0.0007880423,0.0389066,0.00293,0.007141482,0.0008228191,0.01872954],"study_design_scores_gemma":[0.000006253229,0.00004954546,0.8625686,0.00001027463,0.00009599739,0.0001249201,0.0003382189,0.1324847,0.0007453678,0.002814018,0.0007250685,0.00003718833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99804,0.0001086127,0.0009214655,0.0001703971,0.000004999406,0.000002976841,0.0001130519,0.000006294927,0.0006322067],"genre_scores_gemma":[0.999492,0.00009129597,0.00007889909,0.000005446089,0.000006688717,0.000001089127,0.00008652414,0.000001281351,0.0002367475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04147691,"threshold_uncertainty_score":0.08247095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01695859687047646,"score_gpt":0.2117254774316497,"score_spread":0.1947668805611733,"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."}}