{"id":"W2178443321","doi":"10.1162/rest_a_00553","title":"Paving Streets for the Poor: Experimental Analysis of Infrastructure Effects","year":2016,"lang":"en","type":"article","venue":"The Review of Economics and Statistics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Valuation (finance); Residential property; Consumption (sociology); Business; Estimation; Property value; Property (philosophy); Natural resource economics; Agricultural economics; Environmental economics; Economics; Finance; Economic geography; Real estate","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007527297,0.0001296022,0.0006967576,0.000080415,0.00008595778,0.00002010294,0.0002368202,0.00003992717,0.0001013184],"category_scores_gemma":[0.0001991707,0.00007730856,0.0001769392,0.00009250142,0.0001554659,0.00005973986,0.00006859689,0.00003847606,0.000003192048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004224887,"about_ca_system_score_gemma":0.00001916571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003611944,"about_ca_topic_score_gemma":0.0000307139,"domain_scores_codex":[0.9988925,0.00001737849,0.0007314616,0.0001927214,0.00001123333,0.0001546333],"domain_scores_gemma":[0.9977853,0.001092288,0.0007143628,0.0003433736,0.00002821116,0.00003647553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003347593,0.00003775477,0.005932532,0.001503187,0.001406383,1.562479e-7,0.0002222919,0.0002375496,0.0000249835,0.8642184,0.002068974,0.1243143],"study_design_scores_gemma":[0.005226447,0.001073762,0.1081527,0.00371952,0.005677097,0.00001284325,0.0005300911,0.2058847,0.001748535,0.3154287,0.350285,0.002260658],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5139707,0.2961552,0.157908,0.004319233,0.00175396,0.003264526,0.01364971,0.00002780822,0.008950822],"genre_scores_gemma":[0.7299754,0.2661061,0.003438033,0.0003104606,0.00004879426,0.00002909199,0.0000210084,0.0000196774,0.00005148237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5487897,"threshold_uncertainty_score":0.3152552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01678818393471852,"score_gpt":0.2411959901372738,"score_spread":0.2244078062025553,"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."}}