{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003944224,0.0001970574,0.0001883058,0.001437458,0.0005620559,0.0006448888,0.0003850306,0.0002761774,0.001489584],"category_scores_gemma":[0.001078002,0.0001434593,0.0004833574,0.001519413,0.0005820884,0.0004759768,0.000954679,0.0003499538,0.0001131036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001713505,"about_ca_system_score_gemma":0.0006320815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09065758,"about_ca_topic_score_gemma":0.1063669,"domain_scores_codex":[0.9997334,0.00004890237,0.00001339148,0.00005611098,0.00003896053,0.0001092817],"domain_scores_gemma":[0.9994351,0.00005698117,0.0001603823,0.00005159292,0.0001359264,0.0001599367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007684315,0.00005387506,0.9888675,0.00001515443,0.0000780601,0.0001941772,0.001248162,0.0006380861,0.001294545,0.0004345144,0.0004211087,0.006678073],"study_design_scores_gemma":[0.000001994342,0.00001743544,0.998704,0.000002339063,0.000008120763,0.00002145824,0.0004254903,0.0003579599,0.00007971637,0.00005196404,0.0003259099,0.000003637507],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991684,0.00005800914,0.00005327992,0.00009243351,0.000003663784,0.000002863149,0.0000890737,0.000002994237,0.000529385],"genre_scores_gemma":[0.9996767,0.0000327004,0.00003138017,0.00001415075,0.000002411683,0.000002749206,0.00008278171,5.301596e-7,0.0001566434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09065758,"threshold_uncertainty_score":0.1802598,"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."}}