{"id":"W2678907709","doi":"10.5539/ijsp.v6n4p70","title":"Estimating the Common Mean of k Normal Populations with Known Variance","year":2016,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alzahra University","keywords":"Mathematics; Mean squared error; Statistics; Estimator; Equivariant map; Variance (accounting); Minimum-variance unbiased estimator; Bias of an estimator; Best linear unbiased prediction; Econometrics; Computer science","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":[0.0008087252,0.00007982448,0.0001930975,0.00002812701,0.00005401967,0.00001905394,0.0001777548,0.00002191238,0.00003581072],"category_scores_gemma":[0.001500005,0.00003785415,0.00002690817,0.00003514215,0.0002051004,0.0001189672,0.00004253021,0.0001007156,2.0366e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003303244,"about_ca_system_score_gemma":0.00005007777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001480384,"about_ca_topic_score_gemma":0.00005532004,"domain_scores_codex":[0.9988593,0.0001060761,0.0005239262,0.00008668263,0.0003369814,0.0000870185],"domain_scores_gemma":[0.9966221,0.001953989,0.0005233727,0.0001137927,0.0007350255,0.00005174981],"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":[0.0001504478,0.00009035713,0.003443516,0.00003750638,0.00006469937,0.000008439849,0.000272183,0.0002843367,0.00015282,0.8913748,0.00007765854,0.1040433],"study_design_scores_gemma":[0.0004165734,0.0001602939,0.005931617,0.0001460246,0.00003997848,0.00006530872,0.00001480748,0.003836696,0.0001022869,0.9891371,0.0000922445,0.00005713179],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05612621,0.00001795522,0.9424912,0.0006438956,0.0001895231,0.00008632969,0.0002900795,0.000003195167,0.000151547],"genre_scores_gemma":[0.4390952,0.000004788699,0.5608184,0.00001266028,0.00004749585,0.000001364822,6.788627e-7,0.000004069966,0.00001535398],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.382969,"threshold_uncertainty_score":0.1795755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0929094325810015,"score_gpt":0.407992673359975,"score_spread":0.3150832407789735,"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."}}