{"id":"W2342197249","doi":"10.5558/tfc2015-066","title":"Analysis of the log import market and demand elasticity in China","year":2015,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Transport and Economic Policies","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; National Science Foundation","keywords":"Almost ideal demand system; China; Elasticity (physics); Price elasticity of demand; Economics; Error correction model; Business; Agricultural economics; International trade; Geography; Econometrics; Macroeconomics; Microeconomics; Production (economics); Cointegration","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003589452,0.00007208563,0.000152516,0.00007160022,0.00005481586,0.00003185012,0.000199091,0.00002809564,0.00008009894],"category_scores_gemma":[0.0000202084,0.0000418517,0.00005864291,0.0003542837,0.0001265231,0.0002083259,0.00009583968,0.00006827998,0.000004782739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002222025,"about_ca_system_score_gemma":0.00002489829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003147073,"about_ca_topic_score_gemma":0.004754483,"domain_scores_codex":[0.9995062,0.000005448371,0.0001704413,0.00009411786,0.0000691964,0.00015459],"domain_scores_gemma":[0.9996607,0.00001581769,0.0001025445,0.0002016427,0.00001062374,0.000008625029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002276381,0.00001741937,0.9942018,0.00001780165,0.00006343045,5.742602e-7,0.0001223197,0.003008565,0.00001126566,0.001516198,0.0009057206,0.0001121221],"study_design_scores_gemma":[0.000293222,0.000002804071,0.9643837,0.000007409207,0.0001827541,5.017052e-7,0.00008329996,0.03137752,0.00001677584,0.002113573,0.001485357,0.00005309904],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903526,0.0001315274,0.00001270688,0.0005133111,0.00006601664,0.00007784315,0.000003962402,0.00001130425,0.008830692],"genre_scores_gemma":[0.9995703,0.00000648488,0.000002201579,0.0001642403,0.0001024806,0.000003094344,0.000003253013,0.000005288614,0.0001426994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02981813,"threshold_uncertainty_score":0.4757454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0127586806113866,"score_gpt":0.2076002413091697,"score_spread":0.1948415606977831,"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."}}