{"id":"W6959145103","doi":"10.7936/djnk-q162","title":"Interpreting spatial and temporal variations in global air quality using a chemical transport modeling framework","year":2025,"lang":"en","type":"article","venue":"Open Scholarship Institutional Repository (Washington University in St. Louis)","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Air quality index; Particulates; Air pollution; Human health; Satellite; NOx; Climate change; Pollution; Health effect","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007892923,0.0008692109,0.0005295516,0.001096617,0.000777599,0.00227805,0.001287675,0.001858779,0.00176336],"category_scores_gemma":[0.001797962,0.0005552947,0.002112154,0.001321595,0.0005427656,0.001400989,0.001402531,0.00125716,0.0002797892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001724006,"about_ca_system_score_gemma":0.001953049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1405821,"about_ca_topic_score_gemma":0.04927699,"domain_scores_codex":[0.9997603,0.000092444,0.00001614357,0.00007251502,0.00002431369,0.00003425733],"domain_scores_gemma":[0.9995179,0.0002374481,0.00007407842,0.00004128677,0.00008735575,0.00004193062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001308497,0.0000293835,0.00559293,0.00002386315,0.00008321303,0.00005900833,0.00003906907,0.984817,0.0003991723,0.005593963,0.0006640198,0.002685389],"study_design_scores_gemma":[0.000003798335,0.000003867382,0.0004927412,0.000002806738,0.000009255529,0.000004052702,0.00001807876,0.9974625,0.0000349543,0.001440251,0.0005228091,0.000004823797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5582363,0.001817305,0.4010006,0.007709852,0.0004980649,0.000202528,0.009088551,0.00284003,0.01860678],"genre_scores_gemma":[0.9428879,0.0009098027,0.04838009,0.0002808459,0.000171494,0.000175282,0.003249267,0.0002634723,0.0036818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1405821,"threshold_uncertainty_score":0.2795277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02530449451953826,"score_gpt":0.2788168147681996,"score_spread":0.2535123202486613,"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."}}