{"id":"W3121190743","doi":"10.3386/w22804","title":"Trade, Pollution and Mortality in China","year":2016,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Global Health Care Issues","field":"Health Professions","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Canadian Institute for Advanced Research","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institute for Advanced Research","keywords":"China; Pollution; Environmental science; Geography; Biology; Ecology; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004848068,0.0002725581,0.0002201922,0.001221956,0.0004933233,0.0006389085,0.0002802374,0.0003787428,0.001626661],"category_scores_gemma":[0.000799488,0.0001598985,0.0007132826,0.002121943,0.0005105545,0.000365726,0.0006867942,0.0003921266,0.0001580569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001255388,"about_ca_system_score_gemma":0.000990969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1059768,"about_ca_topic_score_gemma":0.1038279,"domain_scores_codex":[0.9997832,0.00002877563,0.00002466687,0.00005643965,0.00003758494,0.00006933681],"domain_scores_gemma":[0.9991307,0.00007690948,0.0004635511,0.00005342098,0.00009566557,0.0001798426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002727561,0.00001164213,0.9974436,0.00001288864,0.00005346996,0.000127838,0.0001658074,0.0002245922,0.0001154105,0.00009986322,0.000204438,0.001513306],"study_design_scores_gemma":[0.000001521238,0.00001165393,0.9993673,0.000006183516,0.00001277732,0.00002048896,0.0001207164,0.0001973028,0.00002384325,0.00004133049,0.0001946166,0.000002244535],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997127,0.0007709723,0.00003862781,0.0004541437,0.00001315331,0.000003121683,0.000675356,0.000004842728,0.0009126546],"genre_scores_gemma":[0.9988034,0.0002481437,0.00001837794,0.00004986665,0.0000144792,0.000002559532,0.0004699275,0.000001160021,0.0003921147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1059768,"threshold_uncertainty_score":0.2107198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4282127672597893,"score_gpt":0.6351057553052308,"score_spread":0.2068929880454415,"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."}}