{"id":"W2081434932","doi":"10.1007/s13369-011-0106-0","title":"Shrinkage Estimation Using Ranked Set Samples","year":2011,"lang":"en","type":"article","venue":"Arabian Journal for Science and Engineering","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Estimator; Shrinkage; RSS; Statistics; Monte Carlo method; Sample (material); Mathematics; Set (abstract data type); Estimation; Shrinkage estimator; Population; Sampling (signal processing); Estimation theory; Computer science; Econometrics; Algorithm; Engineering; Bias of an estimator","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":[],"consensus_categories":[],"category_scores_codex":[0.004946386,0.0001267632,0.0001833249,0.0004433242,0.0004933116,0.0003739385,0.0005431334,0.00003972927,0.00002357017],"category_scores_gemma":[0.003994059,0.00009436718,0.00005788978,0.000732734,0.0001598898,0.001017778,0.00005489896,0.0001337737,0.000005781799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006157147,"about_ca_system_score_gemma":0.000129536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005507759,"about_ca_topic_score_gemma":4.663985e-7,"domain_scores_codex":[0.9982534,0.00001337386,0.0003978807,0.0002761839,0.0006796792,0.0003794623],"domain_scores_gemma":[0.9988151,0.0002659368,0.0001010242,0.00020978,0.0003476621,0.0002605667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007658097,0.00005976991,0.003029079,0.0000767766,0.00006699526,0.00004815848,0.009990541,0.8105246,0.05028718,0.04746072,0.0009035775,0.07747602],"study_design_scores_gemma":[0.0002623198,0.00007766963,0.006412664,0.00005179509,0.00001583524,0.0003186642,0.0002717017,0.976136,0.001270884,0.0143185,0.0006594313,0.0002045608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2584827,0.00009361944,0.7404358,0.00003916275,0.0007213677,0.00009469537,0.000003002336,0.00003068386,0.00009894422],"genre_scores_gemma":[0.8318958,0.000006974432,0.1679668,0.00002138689,0.0000685483,0.000002939617,1.948286e-7,0.000008957995,0.00002849178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.573413,"threshold_uncertainty_score":0.478155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2346127213472306,"score_gpt":0.3513971008261586,"score_spread":0.116784379478928,"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."}}