{"id":"W2964233174","doi":"10.1111/insr.12293","title":"Small Area Quantile Estimation","year":2018,"lang":"en","type":"article","venue":"International Statistical Review","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Project 211; Program of Shanghai Subject Chief Scientist; Yunnan University; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Small area estimation; Quantile; Pooling; Statistics; Estimator; Computer science; Sample size determination; Resampling; Sample (material); Econometrics; Sampling (signal processing); Contrast (vision); Population; Mean squared error; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004740358,0.0006418133,0.001270808,0.001890843,0.0003046026,0.001098125,0.001833387,0.0008986617,0.006959062],"category_scores_gemma":[0.02334669,0.0003632078,0.001111864,0.00236475,0.0006702499,0.001363461,0.001168893,0.00124993,0.001523828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005613225,"about_ca_system_score_gemma":0.0007974105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003019903,"about_ca_topic_score_gemma":0.001847093,"domain_scores_codex":[0.9969446,0.001850805,0.0001145522,0.0004998203,0.0004533895,0.0001367917],"domain_scores_gemma":[0.9921839,0.005542825,0.0005776939,0.000783986,0.0008042887,0.0001073717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001886166,0.0001121138,0.0134548,0.0008551456,0.0005567471,0.0001844266,0.0002522864,0.1297961,0.001335253,0.2248889,0.0178256,0.61055],"study_design_scores_gemma":[0.00007544416,0.000125663,0.00969782,0.0002414457,0.0001762391,0.0002179313,0.0001179626,0.7181441,0.001276325,0.2352573,0.03461658,0.00005321977],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00383409,0.002055778,0.9914869,0.000201909,0.00007046972,0.00005091602,0.0002501353,0.0002988448,0.00175096],"genre_scores_gemma":[0.4227792,0.008137913,0.553285,0.0005329759,0.000744287,0.0006541682,0.002596823,0.0003860459,0.01088359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006959062,"threshold_uncertainty_score":0.02506971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1847528740441207,"score_gpt":0.4619305233138399,"score_spread":0.2771776492697192,"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."}}