{"id":"W3037492211","doi":"10.5705/ss.202018.0499","title":"FUNCTIONAL ADDITIVE QUANTILE REGRESSION","year":2019,"lang":"en","type":"article","venue":"Statistica Sinica","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Natural Science Foundation of China","keywords":"Quantile regression; Econometrics; Regression; Quantile; Statistics; Regression analysis; Computer science; Mathematics","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":[0.005772048,0.001198186,0.001289915,0.001297407,0.0004654005,0.001522613,0.002807973,0.001435625,0.003665415],"category_scores_gemma":[0.01327012,0.0004409981,0.001382374,0.002308774,0.00153607,0.001472651,0.00180441,0.002118131,0.0006524663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001055146,"about_ca_system_score_gemma":0.001095269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004452424,"about_ca_topic_score_gemma":0.002441504,"domain_scores_codex":[0.9957604,0.002715557,0.0000950509,0.0006033144,0.0005839506,0.0002417429],"domain_scores_gemma":[0.9946241,0.003322641,0.0006168953,0.0005757504,0.0007131923,0.0001473586],"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":[0.00009548669,0.0001072863,0.005469589,0.0002669665,0.0002586038,0.0002557989,0.0001501319,0.5815572,0.002238415,0.3332377,0.002405737,0.0739572],"study_design_scores_gemma":[0.00001066334,0.00005899591,0.001057059,0.00001956977,0.0000447894,0.00007325778,0.00002228525,0.9520156,0.0005183773,0.04395679,0.002200536,0.00002205647],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007753421,0.0004282838,0.9899482,0.0002447781,0.00004196543,0.00002180924,0.0000852714,0.0001232939,0.001352963],"genre_scores_gemma":[0.7162766,0.002038477,0.2696987,0.0005665908,0.000359218,0.0002241557,0.0004884681,0.0001813216,0.01016638],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005772048,"threshold_uncertainty_score":0.03052592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1047704351205757,"score_gpt":0.4024661169651799,"score_spread":0.2976956818446042,"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."}}