{"id":"W2766450505","doi":"10.5539/ijsp.v6n6p167","title":"The Exponentiated Kumaraswamy-Weibull Distribution with Application to Real Data","year":2017,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weibull distribution; Exponentiated Weibull distribution; Mathematics; Statistics; Applied mathematics; Weibull fading; Exponential function; Rayleigh distribution; Exponential distribution; Parametric statistics; Probability density function; 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":[],"consensus_categories":[],"category_scores_codex":[0.0008622321,0.00009698152,0.0001379235,0.00001872494,0.0004851178,0.0003567766,0.0008906271,0.00003230908,0.00001917149],"category_scores_gemma":[0.002897081,0.00006362225,0.00001783471,0.00003742435,0.0002390138,0.0001927446,0.0001956923,0.0001275124,0.000005888521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007919558,"about_ca_system_score_gemma":0.00008659295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007561454,"about_ca_topic_score_gemma":0.0001575554,"domain_scores_codex":[0.9987112,0.00004664867,0.0004831569,0.000182472,0.0004599182,0.0001165788],"domain_scores_gemma":[0.9967521,0.0006714368,0.0006313029,0.0006141369,0.001202558,0.0001284399],"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":[0.000192485,0.0001254393,0.002316744,0.0000131543,0.00007533902,0.000004159416,0.00004009379,0.00001120013,0.00005426177,0.9523839,0.008487012,0.03629626],"study_design_scores_gemma":[0.0007274433,0.0001271826,0.209714,0.00004841476,0.00008200249,0.0000539029,0.0000437341,0.01025059,0.00006474386,0.7592703,0.01946432,0.0001533168],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02078406,0.000008275964,0.9688557,0.005913076,0.0001387874,0.0002572031,0.0037674,0.00001064998,0.0002647905],"genre_scores_gemma":[0.9355012,0.00008308081,0.06378859,0.00003504449,0.0001008384,0.00001975775,0.0004174642,0.000007702636,0.0000463615],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9147171,"threshold_uncertainty_score":0.3731183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06861447905215136,"score_gpt":0.3895520487068203,"score_spread":0.320937569654669,"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."}}