{"id":"W2908210970","doi":"10.5539/mas.v13n2p54","title":"The Marshall–Olkin Generalized Inverse Weibull Distribution: Properties and Application","year":2019,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weibull distribution; Mathematics; Statistics; Exponentiated Weibull distribution; Estimator; Applied mathematics; Inverse; Rayleigh distribution; Fisher information; Log-logistic distribution; Exponential function; Exponential distribution; Distribution fitting; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002277857,0.0006973735,0.0006276189,0.001794959,0.0004447747,0.001220811,0.00122211,0.001071894,0.002176347],"category_scores_gemma":[0.007859205,0.000264263,0.0008696968,0.002325413,0.001201883,0.002043578,0.001129623,0.001578246,0.0007305173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001161741,"about_ca_system_score_gemma":0.001010596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003767654,"about_ca_topic_score_gemma":0.00190169,"domain_scores_codex":[0.9989907,0.000295148,0.00004883204,0.0001891173,0.000392548,0.00008367808],"domain_scores_gemma":[0.9975737,0.001119897,0.0003624483,0.0002998999,0.0005708341,0.00007329092],"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":[0.0001112382,0.00004295931,0.008954327,0.0003378035,0.0001123439,0.0008963604,0.0004827347,0.2917546,0.00674067,0.5021237,0.005684154,0.1827592],"study_design_scores_gemma":[0.0000127682,0.00007892337,0.0040942,0.00008348969,0.00005004819,0.001474594,0.0001880945,0.7781881,0.002517439,0.1875081,0.02569419,0.0001100534],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01556273,0.003106527,0.9747215,0.0005026676,0.00009218518,0.00003382886,0.0001426344,0.0002485072,0.005589438],"genre_scores_gemma":[0.7586552,0.00983058,0.2146621,0.0003566897,0.0004912122,0.0002389128,0.0007140018,0.0002750316,0.01477626],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003767654,"threshold_uncertainty_score":0.01204658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05013221205306206,"score_gpt":0.2947071846523546,"score_spread":0.2445749725992925,"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."}}