{"id":"W1558197194","doi":"10.1080/10920277.2003.10596108","title":"“Efficient and Robust Fitting of Lognormal Distributions,” Robert Serfling, October 2002","year":2003,"lang":"en","type":"article","venue":"North American Actuarial Journal","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Log-normal distribution; Statistics; Econometrics; Mathematics; Statistical physics; Computer science; Physics","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":[0.007350421,0.001505084,0.001206194,0.001874659,0.0008362373,0.001962054,0.002180128,0.001609842,0.005474262],"category_scores_gemma":[0.04645904,0.001237608,0.001169131,0.002146722,0.001659532,0.00374327,0.002161836,0.003372719,0.003528735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009968224,"about_ca_system_score_gemma":0.001291184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0110208,"about_ca_topic_score_gemma":0.0124982,"domain_scores_codex":[0.9971114,0.001353943,0.0001223262,0.000310714,0.001010302,0.00009126833],"domain_scores_gemma":[0.9935662,0.003376984,0.0003253059,0.0008113353,0.001810799,0.0001094188],"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":[0.0002189313,0.00006116524,0.003233947,0.0001746906,0.0001280305,0.0001712523,0.0002341736,0.1609228,0.001724558,0.1074581,0.2392031,0.4864693],"study_design_scores_gemma":[0.00003556395,0.00002822372,0.001593363,0.000134046,0.00004345161,0.0003106634,0.0001140989,0.7126184,0.0046754,0.1877524,0.09258617,0.0001083249],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001623339,0.002179604,0.989545,0.003159184,0.0008302514,0.00001885024,0.0001382827,0.0009612104,0.001544289],"genre_scores_gemma":[0.07015944,0.00670543,0.8967448,0.002133304,0.001828045,0.0001339504,0.001022106,0.002027352,0.01924556],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0110208,"threshold_uncertainty_score":0.0388732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05321550713208284,"score_gpt":0.3496902835419041,"score_spread":0.2964747764098213,"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."}}