{"id":"W2910540119","doi":"10.1111/rssb.12309","title":"A General Framework for Quantile Estimation with Incomplete Data","year":2019,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series B (Statistical Methodology)","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Center for Advancing Translational Sciences; Natural Sciences and Engineering Research Council of Canada; China Postdoctoral Science Foundation; National Institutes of Health; University of Alberta; University of Michigan","keywords":"Quantile; Estimation; Computer science; Econometrics; Data mining; Mathematics; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004420281,0.0004014249,0.001238756,0.00003428007,0.0002899999,0.0001220978,0.001249717,0.0003010947,0.0009089683],"category_scores_gemma":[0.04479586,0.0002369376,0.0002273302,0.0002556715,0.0008486936,0.0001793269,0.0004452087,0.001031315,0.00001441321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000113177,"about_ca_system_score_gemma":0.0002769082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000310749,"about_ca_topic_score_gemma":0.000007023831,"domain_scores_codex":[0.9951999,0.001500137,0.001294471,0.0005371229,0.0007977773,0.0006705729],"domain_scores_gemma":[0.9511597,0.04620919,0.0008898654,0.0009353254,0.0004990715,0.000306876],"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":[0.0009287228,0.0001382856,0.000444756,0.0003672731,0.0003111096,0.00001098479,0.0001845693,0.0002356518,0.00006674218,0.9664835,0.01416398,0.01666442],"study_design_scores_gemma":[0.0008703405,0.001297829,0.003965993,0.0001628405,0.0004712255,0.00009149234,0.0002047729,0.1275302,0.00007965574,0.8626817,0.002329178,0.0003146777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003688805,0.00004338851,0.9910093,0.001336707,0.0009582865,0.0006646465,0.002110176,0.00003251993,0.0001562032],"genre_scores_gemma":[0.006869918,0.000009305854,0.9918576,0.0005672295,0.0003317481,0.00002005813,0.00003766377,0.00006466304,0.0002418397],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1272946,"threshold_uncertainty_score":0.9952566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2214770343172296,"score_gpt":0.4360514766702631,"score_spread":0.2145744423530336,"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."}}