{"id":"W2804295110","doi":"10.2298/fil1719965z","title":"Stochastic Volterra integro-differential equations driven by a fractional Brownian motion with delayed impulses","year":2017,"lang":"en","type":"article","venue":"Filomat","topic":"Nonlinear Differential Equations Analysis","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Fractional Brownian motion; Uniqueness; Hurst exponent; Fixed-point theorem; Brownian motion; Mathematical analysis; Stochastic differential equation; Volterra integral equation; Differential equation; Applied mathematics; Integral equation","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009268468,0.0002508519,0.0003205349,0.0001601271,0.0007951204,0.0003407362,0.0003850614,0.000114167,0.002424138],"category_scores_gemma":[0.000589425,0.0002064635,0.0001508351,0.00009725557,0.0001314703,0.0004124929,0.0001046707,0.0002306705,0.0001689023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001051751,"about_ca_system_score_gemma":0.00005885222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002811271,"about_ca_topic_score_gemma":0.0007236481,"domain_scores_codex":[0.9984607,0.00006596291,0.0003654434,0.0003508952,0.0004815976,0.000275416],"domain_scores_gemma":[0.9981362,0.0002643343,0.0004564326,0.0007991095,0.0002200271,0.0001239251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004024591,0.02413338,0.02250937,0.001352535,0.02446172,0.0001910925,0.01485429,0.01205326,0.2191907,0.3653506,0.1582857,0.1535928],"study_design_scores_gemma":[0.004105309,0.0005649125,0.0187908,0.0003025534,0.002183203,0.00004923717,0.0004947046,0.9266258,0.002136022,0.04290168,0.0003833928,0.001462335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2122638,0.000006206386,0.7863075,0.0003152962,0.0001445821,0.0002388719,0.000228575,0.0001020719,0.0003930704],"genre_scores_gemma":[0.9906941,0.000001473749,0.007087266,0.00001903161,0.0002344772,0.00006969041,0.0004755485,0.00004810944,0.001370268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9145726,"threshold_uncertainty_score":0.9984878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03748897265871901,"score_gpt":0.3151673976717686,"score_spread":0.2776784250130496,"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."}}