{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0002803029,0.00008095994,0.000264377,0.00025731,0.0000754583,0.00003783045,0.0001124633,0.00004770165,0.0003312204],"category_scores_gemma":[0.009335218,0.00007272873,0.0000438213,0.0001553437,0.0001600512,0.00007211263,0.000004045675,0.0001016681,0.000006871778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007838786,"about_ca_system_score_gemma":0.0006598402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001364074,"about_ca_topic_score_gemma":0.001057458,"domain_scores_codex":[0.9990576,0.00004370173,0.0005245396,0.00005461406,0.0001277208,0.0001918183],"domain_scores_gemma":[0.9954319,0.002622475,0.000362718,0.0000954241,0.001180759,0.0003067293],"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":[0.000004573294,0.00001761933,0.0004984122,0.0001572605,0.0000438393,0.000006937861,0.0003482825,0.00009088977,0.00005908587,0.9190544,0.03737545,0.0423432],"study_design_scores_gemma":[0.0002862872,0.0002665144,0.004634547,0.00008502467,0.00009510135,0.00003831413,0.0003568532,0.03168768,0.0001757137,0.9619631,0.0003057679,0.0001051352],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01351395,0.00005749767,0.984818,0.00009980806,0.0002387476,0.0001675366,0.0008421564,0.000002307347,0.0002600162],"genre_scores_gemma":[0.2883501,0.000003664572,0.7114779,0.0000291874,0.00003204333,0.000004173611,0.000003051988,0.000008800712,0.0000910392],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2748361,"threshold_uncertainty_score":0.9990095,"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."}}