{"id":"W2080246954","doi":"10.1006/jmva.2000.1954","title":"The Law of the Iterated Logarithm and Central Limit Theorem for L-Statistics","year":2001,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina; Lakehead University","funders":"","keywords":"Law of the iterated logarithm; Mathematics; Iterated logarithm; Central limit theorem; Logarithm; Order statistic; Statistics; Rate of convergence; Applied mathematics; Mathematical analysis; Key (lock)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0119207,0.001358211,0.003032883,0.003999442,0.001630128,0.008045166,0.003036905,0.004205763,0.006497725],"category_scores_gemma":[0.08211779,0.001210404,0.001992861,0.003684009,0.01074134,0.01412092,0.003676247,0.008449405,0.001468186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002671448,"about_ca_system_score_gemma":0.002728726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002328188,"about_ca_topic_score_gemma":0.001249366,"domain_scores_codex":[0.994547,0.002577658,0.0003118503,0.0008034109,0.001412514,0.0003476162],"domain_scores_gemma":[0.9360437,0.05157433,0.002583643,0.003474146,0.00519259,0.001131467],"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":[0.00001494957,0.0000136639,0.0002173099,0.00009101948,0.00003034899,0.00007090282,0.0001206813,0.003735083,0.0002114263,0.9867776,0.001636195,0.007080781],"study_design_scores_gemma":[0.00001181641,0.00001013558,0.0001600472,0.00003096641,0.00001101873,0.0001043421,0.00001561288,0.02245574,0.0001112875,0.9750649,0.002001326,0.00002278009],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01070982,0.008529524,0.9567536,0.004573747,0.0006469573,0.00003475921,0.0002024393,0.0002305036,0.01831867],"genre_scores_gemma":[0.6740234,0.01831217,0.2653668,0.004094822,0.008007806,0.0006769495,0.0006597052,0.000681485,0.02817683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0119207,"threshold_uncertainty_score":0.06304348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06790494807289907,"score_gpt":0.3634088338463151,"score_spread":0.295503885773416,"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."}}