{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003438364,0.0001689622,0.0003203647,0.00004605236,0.00008326567,0.00003309833,0.0001324691,0.00008370059,0.01993304],"category_scores_gemma":[0.004788287,0.0001292531,0.0000593545,0.0001268926,0.0001211398,0.00005600492,0.00007202319,0.0002226988,0.001699664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003088712,"about_ca_system_score_gemma":0.00008879057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008750238,"about_ca_topic_score_gemma":0.000002470841,"domain_scores_codex":[0.998454,0.0001760829,0.0003698835,0.0003536943,0.0003601658,0.0002861187],"domain_scores_gemma":[0.9922124,0.00699679,0.0001411237,0.0003656334,0.0001545611,0.0001294619],"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":[0.00006983742,0.0000828609,0.0002095998,0.0000378047,0.00002130988,0.0000083815,0.00005162569,2.395575e-7,0.000320974,0.8885601,0.08518927,0.02544807],"study_design_scores_gemma":[0.0006231708,0.0003082442,0.01758654,0.0001378925,0.00004341135,0.00001038915,0.0001297386,0.001617564,0.0004203593,0.9601498,0.01868317,0.0002897241],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01416681,0.00003560923,0.8583776,0.0003981863,0.001238001,0.0005056815,0.001456429,0.0001912164,0.1236305],"genre_scores_gemma":[0.3478456,0.00001313575,0.6470844,0.0002172986,0.0001209269,0.00002726335,0.00005852367,0.00003309703,0.004599786],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3336788,"threshold_uncertainty_score":0.9990776,"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."}}