{"id":"W3130040591","doi":"10.1257/pandp.20211074","title":"Changing Population Exposure to Pollution in China’s Special Economic Zones","year":2021,"lang":"en","type":"article","venue":"AEA Papers and Proceedings","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Booth University College","funders":"","keywords":"China; Pollution; Zhàng; Population; Air pollution; Special economic zone; Natural resource economics; Geography; Environmental science; Economics; Environmental health","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":[0.0002427889,0.00006002005,0.00009550282,0.00006328451,0.0002271504,0.00008584328,0.0000469326,0.00005812614,0.0001886325],"category_scores_gemma":[0.00002308015,0.00006245592,0.00002443782,0.0002005002,0.00002637777,0.0002766373,0.00001378266,0.00005113654,0.000004178169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007057169,"about_ca_system_score_gemma":0.00003341583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001438119,"about_ca_topic_score_gemma":0.009788545,"domain_scores_codex":[0.9994016,0.000006221139,0.0001176684,0.0002011136,0.00008200652,0.000191365],"domain_scores_gemma":[0.9998593,0.000004239054,0.00002962101,0.00002448886,0.00001681575,0.00006554982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001488443,0.00001268681,0.9536584,0.000014012,0.000002603787,0.000001722771,0.02121833,0.000002605538,0.0003216387,0.008943673,0.0001015622,0.01570785],"study_design_scores_gemma":[0.000124565,0.00001464018,0.9887221,0.00002068502,0.000004343512,2.999951e-7,0.004506267,0.000004293514,0.00009195452,0.001242252,0.00517751,0.00009106004],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9605829,0.00007109222,0.000001162213,0.002525637,0.0002115922,0.00009682226,0.000002320914,0.00002014189,0.03648837],"genre_scores_gemma":[0.998079,0.00003845913,0.00008154237,0.0001629328,0.0008739502,0.000005168004,0.000005712604,0.000004173924,0.0007490774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03749612,"threshold_uncertainty_score":0.5462238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009495195472408369,"score_gpt":0.250970949032113,"score_spread":0.2414757535597046,"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."}}