{"id":"W3115064918","doi":"10.3386/w28267","title":"Information, Preferences, and Household Demand for School Value Added","year":2020,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University","keywords":"Value (mathematics); Business; Microeconomics; Economics; Computer science; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001481818,0.0001592796,0.0003479717,0.0004018944,0.0002498795,0.001240278,0.0002651446,0.000609924,0.004777591],"category_scores_gemma":[0.007946891,0.0002323747,0.0002626006,0.0005364241,0.0005401346,0.0008627171,0.0003616125,0.0005313372,0.0003243245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007603905,"about_ca_system_score_gemma":0.0002432753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004724876,"about_ca_topic_score_gemma":0.005214537,"domain_scores_codex":[0.9993908,0.0003241894,0.00002776251,0.0000793722,0.00007392787,0.0001037872],"domain_scores_gemma":[0.9925568,0.005175982,0.001404319,0.0003897243,0.0001942464,0.0002788203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000863254,0.0005266911,0.9431316,0.00005456635,0.0001424053,0.0002395131,0.000695875,0.02524395,0.002171565,0.01058925,0.0003753173,0.01596604],"study_design_scores_gemma":[0.0001125064,0.0004068751,0.881115,0.00002824556,0.00006752391,0.0001367781,0.001663828,0.09918711,0.002043824,0.01397625,0.001217259,0.00004491521],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982609,0.00002793265,0.0004815133,0.00008100863,7.518384e-7,0.000005699731,0.0001340499,0.000002856253,0.001005292],"genre_scores_gemma":[0.9994529,0.00001934473,0.0001877161,0.00001015749,0.000001143617,0.000003229563,0.00008076357,6.220526e-7,0.000244108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004777591,"threshold_uncertainty_score":0.01598263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3368703914346666,"score_gpt":0.4044642030501485,"score_spread":0.06759381161548195,"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."}}