{"id":"W2158288838","doi":"10.1016/s2095-3119(12)60055-0","title":"Using Quantile Regression Approach to Analyze Price Movements of Agricultural Products in China","year":2012,"lang":"en","type":"article","venue":"Journal of Integrative Agriculture","topic":"Grey System Theory Applications","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"National Key Research and Development Program of China; Key Technologies Research and Development Program","keywords":"Quantile; Quantile regression; Econometrics; Heteroscedasticity; Sample (material); Confidence interval; Statistics; Linear regression; Regression; Confidence and prediction bands; Regression analysis; Economics; 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":[],"consensus_categories":[],"category_scores_codex":[0.00366783,0.0002625788,0.0007021723,0.0004396154,0.00009557343,0.00007769228,0.0008885249,0.0001195074,0.00003038639],"category_scores_gemma":[0.002825763,0.00009949389,0.0002129537,0.003486069,0.00005231446,0.0009939577,0.0001161767,0.0004267221,0.00001895821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002186011,"about_ca_system_score_gemma":0.00007182323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003436836,"about_ca_topic_score_gemma":0.00001421425,"domain_scores_codex":[0.9959459,0.000603809,0.001440759,0.0002855182,0.001388967,0.000335068],"domain_scores_gemma":[0.9952238,0.000237146,0.00191758,0.0003300969,0.002060089,0.0002312783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001403212,0.001724445,0.05997602,0.00003606734,0.0001367325,0.000002755257,0.03226857,0.002990576,0.8594968,0.009362908,0.0331949,0.000669858],"study_design_scores_gemma":[0.0004333784,0.0001662855,0.8615002,0.0004610069,0.00003858546,0.0002062605,0.04692246,0.00006648104,0.08709288,0.0008928974,0.001942849,0.0002767103],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869618,0.000424375,0.007034965,0.0003505346,0.0003072267,0.0005326479,0.00001681714,0.000005416679,0.004366247],"genre_scores_gemma":[0.9833955,0.000004531973,0.01534923,0.00003362759,0.0002748815,0.000009957211,0.000003682163,0.000006603744,0.000921972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8015242,"threshold_uncertainty_score":0.4057243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07574248865837385,"score_gpt":0.3701716977708142,"score_spread":0.2944292091124404,"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."}}