{"id":"W3122076002","doi":"","title":"Trade, Pollution and Mortality in China","year":2016,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Global Health Care Issues","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Liberian dollar; Pollution; China; Economics; Shock (circulatory); Value (mathematics); Agricultural economics; Demographic economics; International economics; Business; Geography; Biology; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002944502,0.0001192007,0.0002799396,0.0002570017,0.0002383082,0.000007387016,0.0001754503,0.000251953,0.0001485291],"category_scores_gemma":[0.0007213899,0.00009552595,0.0000282117,0.000159996,0.0002033766,0.0001664662,0.000166451,0.0006698619,0.00005633397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00138261,"about_ca_system_score_gemma":0.0004008924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009636139,"about_ca_topic_score_gemma":0.006906834,"domain_scores_codex":[0.9970446,0.0008210812,0.0005855508,0.0004317616,0.0001642493,0.0009528182],"domain_scores_gemma":[0.9986496,0.0006066053,0.0000847121,0.0003999854,0.00002859316,0.0002304905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001087244,0.00006448298,0.8795716,0.0001520139,0.000007874954,0.00001794161,0.001406136,0.000007270698,0.0002706698,0.002932471,0.0003477294,0.1151131],"study_design_scores_gemma":[0.0009616216,0.00006184157,0.9771717,0.0002783523,9.229649e-7,0.000001536521,0.00108422,0.000115157,0.0000170524,0.001910605,0.0182912,0.0001058274],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9378254,0.0001065703,5.725309e-7,0.004345626,0.0002422794,0.0007014042,0.00003704411,0.00002968057,0.05671136],"genre_scores_gemma":[0.9933919,0.005055446,0.0000686147,0.0002505385,0.0001320251,0.0001094297,0.000003157978,0.0000196289,0.0009692644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1150073,"threshold_uncertainty_score":0.3895435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0674063135187359,"score_gpt":0.4560765178953277,"score_spread":0.3886702043765918,"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."}}