{"id":"W2474420501","doi":"10.5539/mas.v10n7p174","title":"A Skewed Truncated Cauchy Uniform Distribution and Its Moments","year":2016,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cauchy distribution; Kurtosis; Mathematics; Skewness; Skew; Log-Cauchy distribution; Ratio distribution; Skew normal distribution; Distribution (mathematics); Variance-gamma distribution; Half-normal distribution; Noncentral chi-squared distribution; Mathematical analysis; Distribution fitting; Range (aeronautics); Probability density function; Applied mathematics; Probability distribution; Statistics; Inverse-chi-squared distribution; Physics; Asymptotic distribution","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002795739,0.0008868898,0.001070667,0.001808019,0.0008026639,0.002091913,0.001484822,0.001548488,0.008347095],"category_scores_gemma":[0.01704122,0.0004797061,0.001077804,0.002329088,0.002529464,0.004041089,0.00124639,0.002110665,0.002015293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001767707,"about_ca_system_score_gemma":0.001170747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003879419,"about_ca_topic_score_gemma":0.001660104,"domain_scores_codex":[0.998409,0.0005253809,0.00007328895,0.0003876176,0.0004343098,0.0001704672],"domain_scores_gemma":[0.993347,0.003563714,0.0008709877,0.0007884955,0.001197417,0.0002323517],"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":[0.00008696953,0.00003884425,0.003841588,0.0001356716,0.00004016454,0.001000533,0.0003420531,0.09542362,0.002709987,0.8512034,0.007069966,0.03810723],"study_design_scores_gemma":[0.00001873629,0.00005574911,0.002711556,0.00008488638,0.00002230023,0.001261339,0.0001882116,0.5789919,0.00149978,0.4049232,0.01015863,0.00008358293],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03022269,0.0008885777,0.9559031,0.0009130014,0.0001490289,0.00008911559,0.0005519449,0.0004014876,0.01088104],"genre_scores_gemma":[0.8190995,0.003508857,0.1423336,0.0008273716,0.0006233772,0.0005513769,0.001908155,0.0003563211,0.03079152],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008347095,"threshold_uncertainty_score":0.02792382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05428637036951604,"score_gpt":0.3301286583891501,"score_spread":0.275842288019634,"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."}}