{"id":"W2805992122","doi":"10.2139/ssrn.2999068","title":"Air Pollution, Health Spending and Willingness to Pay for Clean Air in China","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Willingness to pay; Air pollution; China; Pollution; Environmental science; Natural resource economics; Environmental health; Business; Economics; Political science; Medicine; Chemistry","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":[0.0007691331,0.0003271511,0.0003951577,0.001344877,0.0007574589,0.00123796,0.000593218,0.0009733494,0.004673715],"category_scores_gemma":[0.001211396,0.0003831144,0.001048389,0.002247532,0.0007106991,0.0007093114,0.0008778806,0.0009490548,0.0003974392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002745214,"about_ca_system_score_gemma":0.002988343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2175315,"about_ca_topic_score_gemma":0.2531361,"domain_scores_codex":[0.9993654,0.0000934299,0.00005563212,0.0001001672,0.00007759977,0.0003078399],"domain_scores_gemma":[0.9978194,0.0002932015,0.0007671554,0.00009921742,0.0001884159,0.0008326274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001063997,0.00009814189,0.9967506,0.00001552718,0.000150136,0.0001535352,0.0001917797,0.0005668591,0.00009457468,0.0003785216,0.0003515595,0.001142307],"study_design_scores_gemma":[0.00001187933,0.00005217846,0.9971994,0.000007310482,0.00006750644,0.00003993244,0.00061108,0.001407895,0.00003044675,0.0001814625,0.0003788186,0.00001198463],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983625,0.0001876348,0.00002937664,0.0003792228,0.000006915832,0.000003287679,0.000368645,0.000003429716,0.0006591036],"genre_scores_gemma":[0.9987279,0.00008273933,0.00001264423,0.00003761379,0.000007848772,0.000003489417,0.0003160044,0.000001155238,0.0008106615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2175315,"threshold_uncertainty_score":0.4325308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02376168889017163,"score_gpt":0.3314653661571027,"score_spread":0.3077036772669311,"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."}}