{"id":"W2000994900","doi":"10.1103/physreve.81.016107","title":"Volatility of unevenly sampled fractional Brownian motion: An application to ice core records","year":2010,"lang":"en","type":"article","venue":"Physical Review E","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Fractional Brownian motion; Statistical physics; Brownian motion; Ice core; Volatility (finance); Geology; Mathematics; Econometrics; Physics; Statistics; Climatology","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":[0.003298963,0.000376986,0.000853349,0.001468885,0.0005143596,0.001483728,0.001078147,0.0009308897,0.0005573539],"category_scores_gemma":[0.02000307,0.0003133561,0.000899872,0.001578853,0.0008849457,0.001353219,0.001035159,0.001168884,0.00006175569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000640741,"about_ca_system_score_gemma":0.0003873504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00939038,"about_ca_topic_score_gemma":0.004128897,"domain_scores_codex":[0.999421,0.000308765,0.00003686143,0.00009054572,0.00009170011,0.00005112303],"domain_scores_gemma":[0.9921079,0.006387582,0.0005781097,0.000443996,0.0002671879,0.0002152598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002061563,0.0001138472,0.05589947,0.0001452375,0.0003880061,0.001113867,0.0006575144,0.7519432,0.003516462,0.1342821,0.001578038,0.05015607],"study_design_scores_gemma":[0.000006853031,0.00001048887,0.00459755,0.000006684673,0.00001227971,0.00007643217,0.0000310213,0.9782233,0.0001789131,0.01659757,0.0002464817,0.00001242149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7193006,0.001904429,0.2755975,0.000832053,0.00008459594,0.00004976389,0.0002884644,0.0002288034,0.001713772],"genre_scores_gemma":[0.9773324,0.0007928899,0.02077103,0.00004766744,0.0001178389,0.00002823406,0.0002489902,0.00003566016,0.00062537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00939038,"threshold_uncertainty_score":0.01867145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05702908386252866,"score_gpt":0.3175051530834255,"score_spread":0.2604760692208968,"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."}}