{"id":"W2588902133","doi":"10.1134/s199508021701019x","title":"Combining reliability functions of a Weibull distribution","year":2017,"lang":"en","type":"article","venue":"Lobachevskii Journal of Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"Thammasat University","keywords":"Mathematics; Estimator; Weibull distribution; Statistics; Applied mathematics; Monte Carlo method; Pooling; Mean squared error; Sample size determination; Shrinkage estimator; Efficient estimator; Minimum-variance unbiased estimator; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001087421,0.0001442007,0.0004544168,0.0000434121,0.000339339,0.00007521566,0.0004728627,0.00009391748,0.0001855843],"category_scores_gemma":[0.009060453,0.0001211085,0.0002047558,0.00009703492,0.0002814779,0.0002232272,0.00007951512,0.0002444709,0.00002744362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008821631,"about_ca_system_score_gemma":0.00009411047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004626042,"about_ca_topic_score_gemma":0.000002044422,"domain_scores_codex":[0.9980655,0.00004832751,0.001155272,0.0001084977,0.0004514389,0.000170998],"domain_scores_gemma":[0.9953603,0.000805209,0.002150983,0.0007042554,0.0008397602,0.000139483],"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":[0.00001800535,0.001071264,0.0007328806,0.0003080629,0.00007176088,0.000003608421,0.0002707304,0.00002568224,0.0003145926,0.9873927,0.008581116,0.001209647],"study_design_scores_gemma":[0.001475673,0.000213017,0.0118247,0.000493746,0.0004088457,0.0001741503,0.00097817,0.00594683,0.002057679,0.9738258,0.002340802,0.0002605702],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1140031,0.00002067664,0.8806749,0.0009611836,0.0001684503,0.0001757789,0.0003236879,0.00002396897,0.003648193],"genre_scores_gemma":[0.9332976,0.00001097538,0.06640623,0.0000100552,0.00005556656,0.000006167709,0.00002263585,0.00001256124,0.0001781735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8192945,"threshold_uncertainty_score":0.9992867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07820466112712139,"score_gpt":0.371453543587549,"score_spread":0.2932488824604276,"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."}}