{"id":"W4385702319","doi":"10.1002/cjs.11789","title":"High‐dimensional model averaging for quantile regression","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Shandong University; Jinan Science and Technology Bureau; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canadian Institute for Advanced Research","keywords":"Overfitting; Quantile; Quantile regression; Computer science; Bayesian probability; Data mining; Regression; Machine learning; Artificial intelligence; Algorithm; Econometrics; Mathematics; Statistics; Artificial neural network","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.004857701,0.0008205848,0.001488411,0.000856568,0.0005053445,0.000845117,0.00172696,0.0006775183,0.001412085],"category_scores_gemma":[0.01200007,0.0004628799,0.001241424,0.001473956,0.0007430586,0.000960195,0.001336152,0.001463972,0.0003093156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000654319,"about_ca_system_score_gemma":0.001121962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006116571,"about_ca_topic_score_gemma":0.003566198,"domain_scores_codex":[0.9970837,0.001764074,0.0001153443,0.0004812448,0.0004455202,0.0001101876],"domain_scores_gemma":[0.9952776,0.003149461,0.0003827413,0.0006313359,0.0004739666,0.00008487483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007343489,0.00005100969,0.002624949,0.000165296,0.000330606,0.00009933771,0.00007190679,0.8615201,0.002854063,0.03759532,0.001359114,0.09325489],"study_design_scores_gemma":[0.000002715745,0.00001488535,0.000297541,0.000003596186,0.00001103085,0.00001030207,0.000003774609,0.9898894,0.0003653121,0.009026704,0.0003691799,0.000005667018],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004275704,0.0001972714,0.9950936,0.00006499101,0.00001724983,0.000009467176,0.00003381679,0.0001232027,0.0001847631],"genre_scores_gemma":[0.6012017,0.0008778466,0.3952348,0.0001892906,0.000262353,0.0001886336,0.0005281215,0.0001545342,0.001362681],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006116571,"threshold_uncertainty_score":0.02569032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1531891241941688,"score_gpt":0.3673239034972121,"score_spread":0.2141347793030433,"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."}}