{"id":"W2885284190","doi":"10.5539/ijsp.v7n5p73","title":"The Logarithmic Burr-Hatke Exponential Distribution for Modeling Reliability and Medical Data","year":2018,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weibull distribution; Mathematics; Exponential function; Logarithm; Exponential family; Natural exponential family; Applied mathematics; Exponential distribution; Gamma distribution; Maximum likelihood; Statistics; Mathematical analysis","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002063947,0.00008773499,0.000144301,0.00001655699,0.00025493,0.0001234918,0.0003990263,0.00005866527,0.00005270123],"category_scores_gemma":[0.013019,0.00006150925,0.00002554954,0.00003895397,0.0004662909,0.0001262116,0.0001689291,0.0001442104,0.000001024741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005808158,"about_ca_system_score_gemma":0.000135167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001482438,"about_ca_topic_score_gemma":0.00003503926,"domain_scores_codex":[0.9984758,0.00007168178,0.0006436695,0.000190175,0.0004985596,0.0001200421],"domain_scores_gemma":[0.9961465,0.001680171,0.0002552578,0.0002272746,0.001559693,0.0001310951],"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":[0.0001694619,0.0001193229,0.0001541761,0.00003162587,0.00005089453,0.000001318511,0.00004783509,0.000007777403,0.000009728706,0.9561433,0.004554022,0.03871054],"study_design_scores_gemma":[0.0004147452,0.00006202945,0.0009160896,0.00002227578,0.00003266662,0.00003450566,0.00002367682,0.3609574,0.000009649571,0.6339501,0.003525119,0.00005184386],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02626873,0.00003785269,0.9652481,0.003657441,0.0003106465,0.0002127911,0.004230472,0.000008335408,0.00002562457],"genre_scores_gemma":[0.9083344,0.0001205694,0.09083467,0.00005513206,0.00031375,0.0000125427,0.00031243,0.000006098027,0.00001039708],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8820657,"threshold_uncertainty_score":0.9952947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0922830756832326,"score_gpt":0.4017519182038984,"score_spread":0.3094688425206658,"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."}}