{"id":"W4390940300","doi":"10.1080/10485252.2024.2303418","title":"Generalised local polynomial estimators of smooth functionals of a distribution function with nonnegative support","year":2024,"lang":"en","type":"article","venue":"Journal of nonparametric statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Estimator; Mathematics; Applied mathematics; Kernel density estimation; Mean squared error; Polynomial; Kernel (algebra); Nonparametric statistics; Density estimation; Mathematical optimization; Statistics; Mathematical analysis; Combinatorics","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":[0.0009581137,0.00020251,0.0006646857,0.0004310951,0.00003881764,0.00003522546,0.0001385945,0.0001058248,0.0003772325],"category_scores_gemma":[0.004630377,0.0001455768,0.0001241737,0.001194842,0.0003069785,0.0001263244,0.00002563935,0.000327529,0.000004058274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001473756,"about_ca_system_score_gemma":0.0005294561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002884242,"about_ca_topic_score_gemma":0.000002506256,"domain_scores_codex":[0.9974164,0.0001620819,0.001226845,0.0001732563,0.000811019,0.0002103535],"domain_scores_gemma":[0.9919858,0.005699642,0.0009311225,0.000159784,0.001078195,0.0001454398],"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":[0.003283578,0.001324615,0.002855749,0.002133759,0.001625341,0.0003063001,0.000603066,0.00191169,0.001614471,0.655057,0.09052176,0.2387627],"study_design_scores_gemma":[0.006907593,0.02643213,0.07555398,0.002298891,0.00548154,0.0009336194,0.001250109,0.1496919,0.01443626,0.7102655,0.005292485,0.001455975],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0394693,0.0001301982,0.9578747,0.00003375333,0.000554821,0.000138722,0.001604694,0.00001236566,0.0001814459],"genre_scores_gemma":[0.5439214,0.00002231525,0.4558519,0.00001166046,0.0001039069,0.000002608123,0.0000239556,0.00001871577,0.0000436521],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.504452,"threshold_uncertainty_score":0.5936449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05042780211910258,"score_gpt":0.3409913393116953,"score_spread":0.2905635371925928,"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."}}