{"id":"W2278043303","doi":"","title":"VAR 모형을 이용한 토지시장의 가격예측","year":2015,"lang":"ko","type":"article","venue":"대한부동산학회지","topic":"Energy and Environmental Systems","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Granger causality; Econometrics; Stock (firearms); Yield (engineering); Stock market; Real gross domestic product; Government bond; Interest rate; Quarter (Canadian coin); Error correction model; Real interest rate; Land price; Financial economics; Monetary economics; Macroeconomics; Cointegration; Agricultural economics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009507205,0.0009075946,0.0006720108,0.0007548365,0.000332236,0.001728909,0.001078653,0.0005701869,0.00924561],"category_scores_gemma":[0.00275299,0.0004123963,0.0007633308,0.000906777,0.0004096682,0.001790677,0.0004651721,0.001406615,0.002946017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008195626,"about_ca_system_score_gemma":0.0008048582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01349614,"about_ca_topic_score_gemma":0.007351061,"domain_scores_codex":[0.9994028,0.000100136,0.00003112097,0.0002747085,0.00009545164,0.00009581097],"domain_scores_gemma":[0.9993881,0.0002945095,0.0001032038,0.00004868538,0.0001444269,0.00002110025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002920591,0.0001845014,0.08053869,0.0003427034,0.0007444084,0.0007534412,0.000223972,0.5272853,0.003925071,0.110698,0.01682294,0.258189],"study_design_scores_gemma":[0.00002561479,0.0001640567,0.02017333,0.00004704909,0.0001356979,0.0003016233,0.0001323604,0.939443,0.001019279,0.02647251,0.0120172,0.00006830702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.322785,0.003563351,0.6309897,0.002375477,0.00111694,0.0003098212,0.008394813,0.002807681,0.02765719],"genre_scores_gemma":[0.9223701,0.002247651,0.02423195,0.0002754917,0.0002895085,0.0001944473,0.005985716,0.000139241,0.04426579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01349614,"threshold_uncertainty_score":0.03092963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03777522283837167,"score_gpt":0.2685237096225167,"score_spread":0.230748486784145,"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."}}