{"id":"W7014924031","doi":"","title":"RELATIONSHIP BETWEEN RESIDENTIAL HOUSING PRICE AND RENT ACROSS DIFFERENT REGIONS IN VANCOUVER AND TOKYO","year":2020,"lang":"en","type":"other","venue":"Institutional Repositories DataBase (IRDB)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Work (physics); Government (linguistics); House price; Production (economics); Census; Productivity","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":[0.000182041,0.000269747,0.0003287572,0.001211918,0.0009030685,0.001124477,0.0005165226,0.000188649,0.002212431],"category_scores_gemma":[0.001368076,0.0001928583,0.0004599423,0.003490027,0.0003848662,0.0002923908,0.0007334338,0.0005013914,0.0003345499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00441297,"about_ca_system_score_gemma":0.002272635,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9090628,"about_ca_topic_score_gemma":0.9611892,"domain_scores_codex":[0.9995636,0.00004281855,0.00003392178,0.00009749654,0.0001319855,0.0001300098],"domain_scores_gemma":[0.998693,0.0001067991,0.0002440558,0.00005726801,0.0006144052,0.0002844509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003906739,0.00001265359,0.9941393,0.00001600997,0.0000778461,0.0002244129,0.0003681944,0.0001922664,0.0001234155,0.00009289081,0.0008759649,0.00383803],"study_design_scores_gemma":[0.000001863928,0.00000537776,0.9974942,0.000007768738,0.00001668682,0.00007184145,0.001195041,0.0003673064,0.00002637642,0.00001436697,0.0007926676,0.00000642499],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945522,0.0003796869,0.00009617179,0.0001078374,0.00001098643,0.000009043731,0.002653301,0.00001039197,0.002180263],"genre_scores_gemma":[0.9940255,0.0002745393,0.0001232867,0.00002904859,0.000005486564,0.00001017786,0.00340003,0.000008875761,0.002123085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0909372,"threshold_uncertainty_score":0.1829454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04243632088097421,"score_gpt":0.3031902340393476,"score_spread":0.2607539131583734,"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."}}