{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009573031,0.0002194516,0.0002755914,0.0000402693,0.0003983514,0.0001034769,0.0004432931,0.000302044,0.001627268],"category_scores_gemma":[0.00008557266,0.0002113971,0.0001261595,0.0002890745,0.0003919138,0.0002780266,0.0001372237,0.0002014612,0.006806622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003042078,"about_ca_system_score_gemma":0.0001202521,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008372001,"about_ca_topic_score_gemma":0.001507494,"domain_scores_codex":[0.997632,0.0003528766,0.0003102163,0.0003880424,0.0007335419,0.0005833374],"domain_scores_gemma":[0.9988958,0.00006398548,0.0001328063,0.000342245,0.00002581612,0.0005393882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002371361,0.001331449,0.2321736,0.0001794714,0.0004434246,0.0003779081,0.2136761,0.002149696,0.002011447,0.1498948,0.3513414,0.04618368],"study_design_scores_gemma":[0.0005661782,0.0001506227,0.004189989,0.00007420875,0.00003916645,0.000005641483,0.0157972,0.00007394162,0.000289103,0.002322825,0.9760725,0.0004185568],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.450745,0.002389919,0.00007467671,0.002572693,0.00454992,0.0002686703,0.0000189247,0.0001254031,0.5392548],"genre_scores_gemma":[0.9287053,0.0003223566,0.00007629379,0.0004055435,0.001474453,0.00001447852,0.000009568481,0.00002513748,0.06896683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6247312,"threshold_uncertainty_score":0.9992854,"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."}}