{"id":"W2105430687","doi":"10.1142/s0219025712500233","title":"SOME LINEAR SPDEs DRIVEN BY A FRACTIONAL NOISE WITH HURST INDEX GREATER THAN 1/2","year":2012,"lang":"en","type":"article","venue":"Infinite Dimensional Analysis Quantum Probability and Related Topics","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Hurst exponent; Random field; Stochastic partial differential equation; Connection (principal bundle); Type (biology); Partial differential equation; Gaussian noise; Noise (video); Markov process; Symmetrization; Operator (biology); Pure mathematics; Mathematical analysis; Computer science; Image (mathematics); Algorithm; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007774512,0.0006057335,0.0008524615,0.0008049515,0.0007948001,0.001462347,0.0007534035,0.001384775,0.001345239],"category_scores_gemma":[0.002436975,0.0004029133,0.001175237,0.0003867699,0.002018072,0.001280262,0.001482264,0.001125538,0.0001196339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000944166,"about_ca_system_score_gemma":0.0009041827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003007993,"about_ca_topic_score_gemma":0.001558224,"domain_scores_codex":[0.9996182,0.0001052754,0.00002549997,0.00008573931,0.0000815107,0.0000838011],"domain_scores_gemma":[0.9990097,0.000357756,0.0002718147,0.00003448884,0.0001642375,0.0001619608],"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":[0.000181075,0.00008713554,0.005459097,0.0002268083,0.0001550758,0.002658849,0.0006051366,0.1829408,0.02362383,0.7789054,0.001067267,0.00408958],"study_design_scores_gemma":[0.00006391675,0.00009827987,0.00129534,0.00002556386,0.00003975617,0.0003889384,0.0001969366,0.8671466,0.00248726,0.127292,0.0009089502,0.00005653931],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7230496,0.0007267678,0.2613301,0.001605273,0.0001431006,0.00008754458,0.0001800253,0.0001193383,0.01275817],"genre_scores_gemma":[0.9834571,0.0002940731,0.01016065,0.0001486283,0.0000772433,0.00007049057,0.00008244438,0.0000209013,0.005688342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003007993,"threshold_uncertainty_score":0.006850421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01949565000182499,"score_gpt":0.2180441005600239,"score_spread":0.1985484505581989,"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."}}