{"id":"W4360966999","doi":"10.1016/j.amc.2023.127979","title":"BSDEs generated by fractional space-time noise and related SPDEs","year":2023,"lang":"en","type":"article","venue":"Applied Mathematics and Computation","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Mathematics; Hurst exponent; Uniqueness; Fractional Brownian motion; Stochastic differential equation; Mathematical analysis; Stochastic partial differential equation; Applied mathematics; Brownian motion; Generator (circuit theory); Stochastic process; Differential equation; Physics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001527399,0.00009930175,0.0001889547,0.00007772874,0.0001598337,0.00006838074,0.00004170322,0.00006854372,0.00002453311],"category_scores_gemma":[0.00002217775,0.0001123641,0.00001744772,0.0003047478,0.00004379528,0.00005552886,0.00003464979,0.0000602104,0.0003946001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001259684,"about_ca_system_score_gemma":0.000007096993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001119837,"about_ca_topic_score_gemma":3.210271e-7,"domain_scores_codex":[0.9993166,7.26032e-7,0.000296784,0.0002297457,0.00003262402,0.0001235079],"domain_scores_gemma":[0.9995984,0.00008466697,0.0001766735,0.00007078413,0.00002273663,0.00004667016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000002707347,0.00004303608,0.00002742311,0.00004307431,0.0000193021,3.239903e-7,0.000404134,0.0002114029,0.001300475,0.9938353,0.00114043,0.002972412],"study_design_scores_gemma":[0.0002532253,0.00001537775,0.001156336,0.000007061722,0.000007151936,0.00000437705,0.00007950645,0.1802735,0.00007565291,0.8171278,0.0008608933,0.0001391691],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2248894,0.0004832876,0.7658991,0.0006649785,0.00005468899,0.0002964271,0.00008841995,0.0001479414,0.007475805],"genre_scores_gemma":[0.9793271,0.0001659592,0.01975726,0.00006665813,0.00003927422,0.00009294246,0.0001858534,0.00002618498,0.0003387652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7544377,"threshold_uncertainty_score":0.5071918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01673483753640627,"score_gpt":0.2156313729266142,"score_spread":0.198896535390208,"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."}}