{"id":"W1923220209","doi":"10.22237/jmasm/1036109820","title":"Trimming, Transforming Statistics, And Bootstrapping: Circumventing the Biasing Effects Of Heterescedasticity And Nonnormality","year":2002,"lang":"en","type":"article","venue":"Journal of Modern Applied Statistical Methods","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Statistics; Bootstrapping (finance); Mathematics; Heteroscedasticity; Estimator; Truncated mean; Statistical hypothesis testing; Econometrics; Skewness; Trimming; Robust statistics; Statistic; Test statistic; Type I and type II errors; Computer science","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":[0.003047179,0.0002912863,0.0009436694,0.0001094425,0.0002129497,0.00005943322,0.0001784198,0.0001176211,0.00002522311],"category_scores_gemma":[0.006091544,0.0002068895,0.00008046583,0.0001156527,0.0004980851,0.0001190174,0.00007271867,0.0006367872,1.936724e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003506466,"about_ca_system_score_gemma":0.00002569115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004229188,"about_ca_topic_score_gemma":0.000001196189,"domain_scores_codex":[0.9967696,0.0007522918,0.001314275,0.0002891312,0.0004585669,0.0004161115],"domain_scores_gemma":[0.9768772,0.02175961,0.0007323388,0.0002030287,0.0001666801,0.0002611724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001203987,0.0001336566,0.00001833727,0.001035212,0.0001139428,0.00002846816,0.001269016,0.0000256646,0.01665863,0.3070456,0.0000319348,0.6735192],"study_design_scores_gemma":[0.001183846,0.000255036,0.0004855055,0.0002012159,0.0004421689,0.0001066059,0.0001438518,0.07209595,0.005119171,0.9196368,0.00009028993,0.0002395245],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007145511,0.0006177592,0.9912131,0.00005194615,0.0001400295,0.0003756098,0.00007196225,0.00001363035,0.0003704414],"genre_scores_gemma":[0.3766327,0.00009420617,0.623152,0.0000333664,0.00005126261,0.000005166618,4.347572e-7,0.00002393115,0.000006943115],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6732796,"threshold_uncertainty_score":0.8436708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1251479679364061,"score_gpt":0.4277861735417337,"score_spread":0.3026382056053276,"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."}}