{"id":"W7096627575","doi":"","title":"REAL ESTATE ECONOMICS The Other Side of Eight Mile: Suburban Population and Housing Supply","year":2005,"lang":"en","type":"article","venue":"","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Real estate; Population; Central city; Residential real estate; Mile; Quarter (Canadian coin); Estate; Linkage (software)","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":[0.0003026729,0.00018654,0.0002935446,0.000645912,0.0002594448,0.001510757,0.0002997455,0.0003793169,0.01408101],"category_scores_gemma":[0.001618157,0.0001702471,0.0003085398,0.001414859,0.0008794692,0.001829509,0.0008055818,0.0006492461,0.0009562096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001121366,"about_ca_system_score_gemma":0.0005141694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01626316,"about_ca_topic_score_gemma":0.02705802,"domain_scores_codex":[0.9997718,0.00009758103,0.00001027298,0.00003578631,0.0000393574,0.00004525035],"domain_scores_gemma":[0.9989522,0.0003758428,0.0003422487,0.00006048465,0.000119924,0.0001493026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001183347,0.0001414626,0.8237292,0.0001298568,0.0002119183,0.0004486428,0.001434854,0.03170039,0.0004009044,0.1054217,0.008347586,0.02791518],"study_design_scores_gemma":[0.00003112843,0.0002027041,0.7541776,0.0001848802,0.000130692,0.0005693528,0.009664152,0.03581987,0.0008261934,0.1096437,0.0886999,0.00004981045],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9048873,0.004433024,0.01041844,0.01207994,0.0001192582,0.00002660472,0.002040364,0.00003578247,0.06595932],"genre_scores_gemma":[0.9892551,0.0009993617,0.0004466069,0.0002372364,0.00007426763,0.00000947447,0.0003192787,0.0000100495,0.008648582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01626316,"threshold_uncertainty_score":0.04710567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01945982251164968,"score_gpt":0.1983397623756338,"score_spread":0.1788799398639841,"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."}}