{"id":"W2132277317","doi":"10.1002/cjs.11191","title":"Fast nonparametric estimation for convolutions of densities","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Convolution (computer science); Mathematics; Kernel (algebra); Kernel density estimation; Convergence (economics); Nonparametric statistics; Statistics; Applied mathematics; Computer science; Combinatorics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007636375,0.0005545933,0.001012672,0.00156618,0.0004113794,0.001249305,0.001351857,0.001141454,0.001565205],"category_scores_gemma":[0.04050199,0.0005969375,0.0009381718,0.001136542,0.001729115,0.002235231,0.002014955,0.001755204,0.0003282014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00091076,"about_ca_system_score_gemma":0.001044598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003493528,"about_ca_topic_score_gemma":0.001630891,"domain_scores_codex":[0.9976042,0.00135254,0.0000925707,0.0002959433,0.0005269851,0.0001278815],"domain_scores_gemma":[0.9808137,0.01521576,0.00110815,0.001373647,0.001283929,0.0002048676],"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":[0.0003867844,0.00009658914,0.005881435,0.0003072007,0.000193395,0.0002505955,0.0003078653,0.5129787,0.0100244,0.2661602,0.001921769,0.2014911],"study_design_scores_gemma":[0.000009617508,0.00002085676,0.0008071995,0.00001673516,0.000007458802,0.00007682646,0.00001135132,0.9596608,0.001038548,0.03781676,0.000519134,0.00001474657],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01069601,0.0001182309,0.9886829,0.00006386563,0.00001307868,0.00001249373,0.00001757183,0.0001070852,0.0002886519],"genre_scores_gemma":[0.4861733,0.0004949137,0.5101201,0.000132185,0.0001165663,0.0001365979,0.0002486445,0.000151717,0.002426039],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007636375,"threshold_uncertainty_score":0.04038548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08868029858986207,"score_gpt":0.3264523011718845,"score_spread":0.2377720025820224,"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."}}