{"id":"W3091993350","doi":"10.1002/cjs.11572","title":"Efficient nonparametric estimation for skewed distributions","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada; University of Ottawa","funders":"","keywords":"Estimator; Mean squared error; Mathematics; Statistics; Bias of an estimator; Efficient estimator; Efficiency; Nonparametric statistics; Consistent estimator; Context (archaeology); Econometrics; Minimum-variance unbiased estimator; Conditional expectation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0002825961,0.0001038216,0.0002646996,0.000106334,0.0001451545,0.00003806556,0.000128307,0.00004610605,0.00005495645],"category_scores_gemma":[0.01587686,0.00009615567,0.0000602924,0.0002384781,0.00007420731,0.00002836009,0.00000546436,0.0001575374,0.00000403276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001264229,"about_ca_system_score_gemma":0.0005885611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004058537,"about_ca_topic_score_gemma":0.0001516131,"domain_scores_codex":[0.9989741,0.00004307735,0.0004782725,0.0001003669,0.0001487362,0.0002554441],"domain_scores_gemma":[0.9966174,0.001719548,0.0002749669,0.00008115808,0.0004925061,0.0008143578],"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":[0.00002475318,0.00002240535,0.00001655897,0.0001132046,0.00003336726,0.00005280116,0.0003268683,0.008954619,0.00002993166,0.9404379,0.01644883,0.03353879],"study_design_scores_gemma":[0.0005214553,0.000284099,0.00009586305,0.00003236235,0.0001246104,0.00002257932,0.00006605253,0.3394824,0.00007162673,0.6553078,0.003853581,0.0001376396],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001016183,0.00005762747,0.9940229,0.0007021149,0.0001985589,0.0001958933,0.003718987,0.000006370551,0.00008134836],"genre_scores_gemma":[0.1912788,0.000002012857,0.8084673,0.000117448,0.00008078585,0.000003669243,0.00001900991,0.00001507744,0.00001596345],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3305277,"threshold_uncertainty_score":0.9924128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1169882899278286,"score_gpt":0.3822802208548926,"score_spread":0.265291930927064,"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."}}