{"id":"W2000956261","doi":"10.1111/j.1368-423x.2009.00285.x","title":"Finite-sample distribution-free inference in linear median regressions under heteroscedasticity and non-linear dependence of unknown form","year":2009,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Heteroscedasticity; Mathematics; Statistics; Nuisance parameter; Inference; Linear regression; Monte Carlo method; Parametric statistics; Asymptotic distribution; Linear model; Applied mathematics; Econometrics; Estimator; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001102363,0.0001725671,0.0004346085,0.0004229551,0.0001280209,0.0000546369,0.0003511455,0.0001292634,0.0001842752],"category_scores_gemma":[0.06906261,0.0001447191,0.00006585495,0.0008140757,0.0001113326,0.00021166,0.00010964,0.0005584243,0.000003314399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009635274,"about_ca_system_score_gemma":0.0001189025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002490958,"about_ca_topic_score_gemma":0.00004463342,"domain_scores_codex":[0.9983234,0.00007767454,0.0008004635,0.0002150311,0.0002436081,0.0003397804],"domain_scores_gemma":[0.9862968,0.01251844,0.0004017009,0.0002905075,0.0002062248,0.0002863507],"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":[0.0002472344,0.002123736,0.2043305,0.0003879486,0.0001387516,0.0001095374,0.001391064,0.00453388,0.0003194114,0.637734,0.0009673755,0.1477166],"study_design_scores_gemma":[0.0008760061,0.0003590056,0.05911289,0.0001809229,0.00002235393,0.00001423809,0.00006913792,0.06608877,0.0003018767,0.87269,0.00006754661,0.000217287],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1479378,0.00006521959,0.8509407,0.0003110917,0.0001796411,0.00009636374,0.0002578066,0.000008596693,0.0002027595],"genre_scores_gemma":[0.7652236,0.0002458906,0.2343777,0.00005645154,0.00006759463,0.000002074418,0.000006952514,0.000007165437,0.00001263629],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6172857,"threshold_uncertainty_score":0.9387791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1303452266968345,"score_gpt":0.3819127676770376,"score_spread":0.2515675409802032,"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."}}