{"id":"W2605441625","doi":"","title":"Do Efforts to Mitigate Gentrification Work? Evidence from Washington DC","year":2017,"lang":"en","type":"article","venue":"Alternate routes","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Gentrification; Work (physics); Political science; Economics; Engineering; Economic growth; Mechanical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002585592,0.0002980116,0.0004246728,0.001176923,0.003238085,0.002299485,0.001800567,0.001549036,0.006141033],"category_scores_gemma":[0.008516286,0.0002926214,0.0004987243,0.002476461,0.00167585,0.001360955,0.002543724,0.002045329,0.0003931848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003062303,"about_ca_system_score_gemma":0.00735086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4100655,"about_ca_topic_score_gemma":0.7240508,"domain_scores_codex":[0.9976457,0.0009312612,0.0000751024,0.000207094,0.0002689823,0.000871871],"domain_scores_gemma":[0.9946837,0.001423997,0.00140938,0.0005512542,0.000821133,0.001110518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007086801,0.001738534,0.8119709,0.0004720034,0.000938222,0.0003772486,0.01141432,0.0006315231,0.0002427824,0.02802424,0.03868925,0.1047923],"study_design_scores_gemma":[0.0002873325,0.0003237229,0.9051571,0.001227944,0.001033591,0.00009176898,0.03671563,0.0003846596,0.0004016679,0.003252827,0.05108352,0.00004021447],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9486824,0.004127029,0.0002259816,0.009612276,0.0002486042,0.00004980151,0.0007316686,0.0000100004,0.03631224],"genre_scores_gemma":[0.98948,0.002364711,0.0001479535,0.002161331,0.00005468336,0.00004440675,0.0003637348,0.000007135915,0.005376031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4100655,"threshold_uncertainty_score":0.8153573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07473838240047094,"score_gpt":0.3452801662210165,"score_spread":0.2705417838205456,"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."}}