{"id":"W3122209630","doi":"10.6084/m9.figshare.6295001.v1","title":"Conditional Extremes in Asymmetric Financial Markets","year":2018,"lang":"en","type":"dataset","venue":"Figshare","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Financial market; Economics; Financial economics; Business; Econometrics; Financial system; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001765444,0.0006081649,0.0006451885,0.001733638,0.0003384702,0.001226518,0.001404643,0.001200743,0.00524304],"category_scores_gemma":[0.007192668,0.0002074204,0.0008338841,0.00186604,0.0003923235,0.0010186,0.001096312,0.0009597812,0.002768303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006174819,"about_ca_system_score_gemma":0.0003519432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007281021,"about_ca_topic_score_gemma":0.01024708,"domain_scores_codex":[0.9994424,0.0002181413,0.00004683621,0.0001504057,0.00007695579,0.00006528463],"domain_scores_gemma":[0.9987137,0.0005779623,0.0001929559,0.0003307428,0.0001241599,0.00006040555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001026563,0.0003946344,0.113057,0.001070233,0.000398093,0.0008098509,0.0002697925,0.1310258,0.0006414743,0.02117071,0.6576427,0.07249326],"study_design_scores_gemma":[0.0009252474,0.0002263615,0.143904,0.0005392051,0.0001685653,0.001657963,0.0006176413,0.4592454,0.001800779,0.1028425,0.2878801,0.0001921319],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2384758,0.002682775,0.01531511,0.002461919,0.0002798798,0.0001612679,0.7310559,0.003225783,0.006341702],"genre_scores_gemma":[0.3195859,0.0007722949,0.01017358,0.000264581,0.0001205109,0.0002460925,0.6668844,0.0001294288,0.00182322],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007281021,"threshold_uncertainty_score":0.01753968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04647933431681254,"score_gpt":0.2289281504525029,"score_spread":0.1824488161356903,"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."}}