{"id":"W2605293422","doi":"10.5430/ijfr.v8n2p145","title":"Home Bias and the Real Estate Prices","year":2017,"lang":"en","type":"article","venue":"International Journal of Financial Research","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Chiao Tung University; Shanghai Educational Development Foundation","keywords":"Economics; Proxy (statistics); Real estate; Econometrics; Preference; Information asymmetry; Marginal utility; Microeconomics; Investment (military); Financial economics; Monetary economics; Finance; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003427671,0.0001731026,0.0001816927,0.0002728509,0.0001466796,0.0010638,0.000184066,0.0003342732,0.003394587],"category_scores_gemma":[0.003219297,0.0001158042,0.0002746981,0.0003412002,0.000523244,0.001237854,0.0004387063,0.0004899047,0.000246956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005007185,"about_ca_system_score_gemma":0.0001966366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001157431,"about_ca_topic_score_gemma":0.001064738,"domain_scores_codex":[0.9997658,0.00006970961,0.00001273068,0.00004511069,0.00006961089,0.00003696132],"domain_scores_gemma":[0.9983164,0.0006537843,0.0006681283,0.0001450401,0.000127173,0.00008950179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007125976,0.0006162397,0.5962759,0.0002016554,0.0004146837,0.002375855,0.001479584,0.04493512,0.01533457,0.2386029,0.00113578,0.09791511],"study_design_scores_gemma":[0.00004214902,0.0003123468,0.6757637,0.00004047043,0.0001431671,0.001214965,0.00138379,0.08202571,0.006888011,0.2267427,0.005372073,0.00007084833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774472,0.0003808662,0.01213307,0.0002346297,0.00001310532,0.000009967943,0.00006685166,0.00001493676,0.009699469],"genre_scores_gemma":[0.9988027,0.00007532327,0.0003357599,0.000008601675,0.000006368504,0.000001658392,0.00001218848,0.00000160924,0.0007559761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003394587,"threshold_uncertainty_score":0.011356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.151193584140327,"score_gpt":0.3647140047400172,"score_spread":0.2135204205996901,"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."}}