{"id":"W1920288580","doi":"10.1002/cjs.11199","title":"Robust small area estimation under semi‐parametric mixed models","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Small area estimation; Mathematics; Estimator; Outlier; Mixed model; Statistics; Parametric statistics; Best linear unbiased prediction; Generalized linear mixed model; Mean squared error; Random effects model; Linear regression; Restricted maximum likelihood; Linear model; Econometrics; Estimation theory; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005658384,0.0002113012,0.0004725245,0.0003863559,0.0001398568,0.0001351208,0.0002552618,0.0001147096,0.000451215],"category_scores_gemma":[0.004033246,0.0001843887,0.00007428011,0.0002851772,0.0001210404,0.0002708406,0.00001316968,0.0003688127,0.00002367359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002585141,"about_ca_system_score_gemma":0.0006848972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001042265,"about_ca_topic_score_gemma":0.00320467,"domain_scores_codex":[0.9980631,0.0001409568,0.0008891229,0.0001691271,0.0002884063,0.0004493039],"domain_scores_gemma":[0.9952298,0.002102289,0.0005390194,0.0002505018,0.0009079664,0.000970387],"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":[0.000007330886,0.00003833786,0.00004907868,0.00008295058,0.00007596453,0.0001147405,0.0003019,0.1828289,0.00001935055,0.7429289,0.02597917,0.0475734],"study_design_scores_gemma":[0.0002328931,0.00007618268,0.0002193341,0.00004983093,0.00006203314,0.00006925083,0.0001280382,0.3017889,0.00001429048,0.6970467,0.0001628662,0.0001496829],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007703495,0.00009843458,0.9903617,0.000202661,0.000353754,0.000209787,0.0003396169,0.000009052751,0.0007215298],"genre_scores_gemma":[0.2010509,0.00001429223,0.7984058,0.0001401465,0.00005316026,0.000005247637,0.0000105831,0.00003528141,0.0002846215],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1933474,"threshold_uncertainty_score":0.7519153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2233574623761498,"score_gpt":0.3353689594718339,"score_spread":0.1120114970956841,"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."}}