{"id":"W1991689869","doi":"10.1080/00949651003587684","title":"Pitman closeness, monotonicity and consistency of best linear unbiased and invariant estimators for exponential distribution under Type II censoring","year":2010,"lang":"en","type":"article","venue":"Journal of Statistical Computation and Simulation","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; McMaster University","funders":"","keywords":"Mathematics; Estimator; Statistics; Monotonic function; Exponential distribution; Best linear unbiased prediction; Applied mathematics; Exponential function; Exponential family; Censoring (clinical trials); Mathematical analysis; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003626034,0.0001092528,0.0002602437,0.00005958348,0.0002211499,0.00003820378,0.00003100313,0.000082194,0.00002353024],"category_scores_gemma":[0.002112514,0.000100219,0.00002582901,0.00009830428,0.0001978905,0.0001284522,0.00002412818,0.0001459877,4.006109e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001861106,"about_ca_system_score_gemma":0.00005039275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008374975,"about_ca_topic_score_gemma":0.000004912449,"domain_scores_codex":[0.9988837,0.00005039541,0.0006397456,0.0001380075,0.0001842225,0.0001039633],"domain_scores_gemma":[0.9967106,0.00208266,0.0003951436,0.00005829139,0.0006159103,0.0001374192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001797574,0.0001789991,0.0004048744,0.0001638199,0.00003324655,0.000001208098,0.0001443416,0.007513595,0.00142145,0.9810915,0.00008248424,0.008784733],"study_design_scores_gemma":[0.001135664,0.0002278646,0.01779779,0.0000394418,0.0001267184,0.00001810649,0.00008465967,0.7985176,0.0001707684,0.1816785,0.00010084,0.0001020315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3878408,0.00001052592,0.6115892,0.0001195879,0.00005788725,0.0001577667,0.0002086253,0.00000685595,0.000008684788],"genre_scores_gemma":[0.8758413,0.00001003209,0.1239378,0.00001786787,0.00003646304,0.000002905476,0.0001423845,0.000007736896,0.000003532305],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.799413,"threshold_uncertainty_score":0.4086813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06994560413086628,"score_gpt":0.3902781892488038,"score_spread":0.3203325851179375,"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."}}