{"id":"W1934816454","doi":"10.3968/7482","title":"Macroeconomic Drivers of House Prices in Malaysia","year":2015,"lang":"en","type":"article","venue":"Canadian social science","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Inflation (cosmology); Monetary economics; Money supply; House price; Stock (firearms); Stock market; Economic bubble; Inflation rate; Interest rate; Macroeconomics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009376915,0.00007378438,0.0002192349,0.0004785069,0.00009464243,0.00006448158,0.000417662,0.00006139685,0.00008552011],"category_scores_gemma":[0.00008322602,0.0001034276,0.00003828572,0.0004873318,0.0003885835,0.0003743096,0.00003599516,0.00007158543,0.000263848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001091299,"about_ca_system_score_gemma":0.0004937203,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03647316,"about_ca_topic_score_gemma":0.03338974,"domain_scores_codex":[0.9989945,0.000003736248,0.0003041435,0.0002649586,0.00002411057,0.0004085329],"domain_scores_gemma":[0.9993612,0.000009785658,0.0001593716,0.0001314684,0.00002541045,0.0003128199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005066576,0.00001395391,0.7801178,0.000006621243,0.000004380395,0.000005600757,0.003748873,0.00008638401,0.00001369576,0.2124358,0.001036407,0.00252543],"study_design_scores_gemma":[0.00295981,0.0001583865,0.5531557,0.00003496017,0.000009788719,0.00000835807,0.01149536,0.01149488,0.000305348,0.09162125,0.3268802,0.001875925],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6461042,0.00002618512,0.00001182536,0.0001871412,0.0002654569,0.00005527158,0.00002236696,0.000009019239,0.3533185],"genre_scores_gemma":[0.9994699,0.00001889551,0.0002151224,0.0001520688,0.0000573682,0.000002998706,8.74657e-7,0.00001141182,0.00007138136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3533656,"threshold_uncertainty_score":0.9842484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02890884624982216,"score_gpt":0.2138266033987719,"score_spread":0.1849177571489498,"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."}}