{"id":"W4401958719","doi":"10.1038/s44284-024-00115-8","title":"Health co-benefits of post-COVID-19 low-carbon recovery in Chinese cities","year":2024,"lang":"en","type":"article","venue":"Nature Cities","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Environmental science; Business; Environmental health; Natural resource economics; Medicine; Virology; Economics; Disease; Outbreak","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":[0.0005556719,0.0003484197,0.0002909195,0.0008926326,0.001062959,0.0009237486,0.0006972715,0.0007183785,0.002883337],"category_scores_gemma":[0.0009681124,0.0001520504,0.0009045007,0.001544552,0.00072354,0.0005339039,0.001436412,0.0005434342,0.0001259288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005794923,"about_ca_system_score_gemma":0.006772749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2678659,"about_ca_topic_score_gemma":0.4411142,"domain_scores_codex":[0.9992472,0.0001050338,0.00003833982,0.00007785366,0.00008443249,0.0004471473],"domain_scores_gemma":[0.9990001,0.00006441939,0.0002740236,0.00006001587,0.0002530215,0.0003483887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009393832,0.0005169681,0.9725595,0.0001443429,0.0003570175,0.000836682,0.000734481,0.003036642,0.001202064,0.001263788,0.002103858,0.01630526],"study_design_scores_gemma":[0.0000194065,0.0001220832,0.9960905,0.00001330608,0.0001357678,0.00003151954,0.001119457,0.0009424908,0.0002285969,0.000179379,0.001103771,0.00001367657],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965563,0.0003662777,0.00005539153,0.0009040496,0.00002207972,0.0000234683,0.0005599956,0.000008062575,0.001504367],"genre_scores_gemma":[0.9989399,0.0001053663,0.00002432921,0.00008605881,0.00001278777,0.00000992625,0.0002961794,0.000001099074,0.0005244953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2678659,"threshold_uncertainty_score":0.5326134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02059285159607585,"score_gpt":0.3331043472643063,"score_spread":0.3125114956682305,"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."}}