{"id":"W2573621420","doi":"","title":"A short note on quantile and expectile estimation in unequal probability samples","year":2016,"lang":"en","type":"article","venue":"Survey methodology","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quantile; Estimator; Mathematics; Quantile regression; Statistics; Econometrics; Generalization","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02193238,0.0001398563,0.0004355568,0.0002049816,0.0000713211,0.00003118838,0.0002618236,0.0001140468,0.00006116289],"category_scores_gemma":[0.2231894,0.00008647359,0.00002660874,0.0004355986,0.0002673745,0.0002203197,0.0001181703,0.00013973,0.00004014394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007342274,"about_ca_system_score_gemma":0.00004484262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002548441,"about_ca_topic_score_gemma":0.001319617,"domain_scores_codex":[0.9913634,0.006474609,0.0006392887,0.0007424284,0.0004685459,0.0003117178],"domain_scores_gemma":[0.9029201,0.09629017,0.0001104256,0.0003979091,0.0001922863,0.00008914858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005527586,0.00005107555,0.2177766,0.000006862901,0.000003543304,0.000005455206,0.0004003558,0.0006365833,0.002357143,0.00670201,0.00003753016,0.7714701],"study_design_scores_gemma":[0.000178398,0.00009974116,0.69749,0.00001197514,0.000001371781,0.00000170905,0.00005818762,0.0009538662,0.001688282,0.2993432,0.00006988418,0.0001034161],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.40076,0.00001892705,0.5986572,0.00009399857,0.0002393222,0.0001111289,0.00004413533,0.00002005137,0.00005524106],"genre_scores_gemma":[0.7329708,0.000003053894,0.2669273,0.00001604077,0.00001947618,0.00002183946,0.000002290982,0.000007440435,0.0000317358],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7713667,"threshold_uncertainty_score":0.783354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6814941744892106,"score_gpt":0.5625075198466303,"score_spread":0.1189866546425803,"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."}}