{"id":"W2990181566","doi":"10.3386/t0339","title":"Unconditional Quantile Regressions","year":2007,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Canadian Institute for Advanced Research","funders":"","keywords":"Quantile regression; Econometrics; Quantile; Statistics; Cross-sectional regression; Mathematics; Logistic regression; Estimator; Logit; Ordinary least squares; Regression analysis; Nonparametric statistics; Binomial regression; Nonparametric regression; Ordered logit; Censored regression model; Polynomial regression","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005249819,0.0009059358,0.001222049,0.001744249,0.0003814723,0.001126467,0.002658081,0.0007296859,0.01081796],"category_scores_gemma":[0.02757115,0.0004986865,0.001417177,0.002346123,0.0007430543,0.001681574,0.001867058,0.002314155,0.001802717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007716748,"about_ca_system_score_gemma":0.001105272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005347292,"about_ca_topic_score_gemma":0.003536525,"domain_scores_codex":[0.9959853,0.002090346,0.0001426713,0.0006775305,0.000808506,0.0002955978],"domain_scores_gemma":[0.9921986,0.004477378,0.0009284721,0.001401236,0.0008451493,0.0001490853],"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":[0.0002379084,0.0002265873,0.03581947,0.0004444542,0.0008494506,0.0002903417,0.0003580904,0.2140414,0.003013354,0.3781839,0.01676396,0.3497712],"study_design_scores_gemma":[0.00007752048,0.0001446035,0.02016452,0.0001212656,0.0003164209,0.0002337864,0.00008812446,0.7623993,0.003830783,0.1848624,0.0276683,0.00009291364],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0131292,0.000639786,0.980243,0.0003635274,0.00009141243,0.00006567947,0.000768395,0.00106539,0.003633615],"genre_scores_gemma":[0.6606426,0.002413077,0.3145782,0.0006269729,0.0006458458,0.0006400392,0.002814441,0.0008041682,0.01683463],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01081796,"threshold_uncertainty_score":0.03618962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7239146134141636,"score_gpt":0.6561762839538734,"score_spread":0.06773832946029024,"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."}}