{"id":"W2093972316","doi":"10.1007/s10463-006-0042-z","title":"Wavelet-Based Estimation for Univariate Stable Laws","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Wavelet; Univariate; Context (archaeology); Parametric statistics; Algorithm; Mathematics; Domain (mathematical analysis); Computer science; Inference; Mathematical optimization; Artificial intelligence; Statistics; Multivariate 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":[0.003498066,0.0006999509,0.001229802,0.001659154,0.0003527801,0.0014818,0.001361318,0.001339854,0.001455322],"category_scores_gemma":[0.01725962,0.0009661944,0.0008343318,0.001248763,0.001607943,0.003289502,0.001525677,0.00205356,0.0003199153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007986101,"about_ca_system_score_gemma":0.0009996088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002419278,"about_ca_topic_score_gemma":0.002260952,"domain_scores_codex":[0.9994547,0.0002058171,0.00003290945,0.0001170088,0.0001383925,0.00005121307],"domain_scores_gemma":[0.9931327,0.005322493,0.0004561561,0.0003932803,0.0005463791,0.0001490576],"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":[0.0001915414,0.000103976,0.001784088,0.0002155401,0.000124317,0.0001117921,0.0002051284,0.5379225,0.009121116,0.3421183,0.002126729,0.105975],"study_design_scores_gemma":[0.000003967451,0.000006281386,0.0001575389,0.000004529541,0.000005164927,0.000007980066,0.000004026563,0.9729308,0.0004801421,0.02618048,0.0002118138,0.000007143441],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01446654,0.0001822673,0.9846475,0.0001271871,0.00002156382,0.000008869045,0.00003277117,0.00008486498,0.0004284772],"genre_scores_gemma":[0.625206,0.001941032,0.3621324,0.0001617891,0.0002937616,0.0001087439,0.0006251072,0.0003203761,0.009210866],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003498066,"threshold_uncertainty_score":0.01849973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05950508309257805,"score_gpt":0.3350685135756649,"score_spread":0.2755634304830868,"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."}}