{"id":"W1755189647","doi":"10.1111/jtsa.12139","title":"On Uniqueness of Moving Average Representations of Heavy‐tailed Stationary Processes","year":2015,"lang":"en","type":"article","venue":"Journal of Time Series Analysis","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Economic and Social Research Council; Agence Nationale de la Recherche","keywords":"Mathematics; Uniqueness; Sequence (biology); Moving average; Distribution (mathematics); Stable distribution; Stationary process; Stationary sequence; Heavy-tailed distribution; Gaussian; Identification (biology); Statistical physics; Attraction; Mathematical analysis; Applied mathematics; Statistics; Stochastic process","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":[],"consensus_categories":[],"category_scores_codex":[0.0006313958,0.00009272505,0.000583541,0.0002948858,0.00003376626,0.000009750478,0.0001262415,0.00003525673,0.000142576],"category_scores_gemma":[0.004136838,0.00007199115,0.0001712135,0.0007277966,0.00006942209,0.0002805321,0.00002682526,0.00009110161,9.478599e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003444366,"about_ca_system_score_gemma":0.0001700873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001370704,"about_ca_topic_score_gemma":0.000009928799,"domain_scores_codex":[0.9984667,0.0001618225,0.0007694516,0.00009392011,0.000415977,0.00009211871],"domain_scores_gemma":[0.9960954,0.00123996,0.0009849345,0.0001820318,0.001405254,0.00009241854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003554153,0.001721115,0.003671993,0.001532373,0.007621693,0.000129093,0.008060782,0.7965595,0.005774831,0.1623958,0.002636521,0.006342156],"study_design_scores_gemma":[0.0006626254,0.0007495586,0.0003163338,0.0001775,0.002003012,0.00001789073,0.001756024,0.01006355,0.01498295,0.9689908,0.00009890131,0.0001808621],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08355717,0.00007384564,0.9152195,0.0001645195,0.00002172171,0.00006266595,0.00005986082,0.000005815049,0.0008349475],"genre_scores_gemma":[0.4282729,0.00005528077,0.5707219,0.00001517842,0.00002492244,0.000002181343,0.000006841709,0.00001279665,0.0008879469],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.806595,"threshold_uncertainty_score":0.495248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07383410621376543,"score_gpt":0.4093354553072189,"score_spread":0.3355013490934535,"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."}}