{"id":"W4408187051","doi":"10.1016/j.atmosenv.2025.121163","title":"Spatial and seasonal variations and trends in carbon monoxide over China during 2013–2022","year":2025,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Tsinghua University; National Key Research and Development Program of China; National Aeronautics and Space Administration","keywords":"Carbon monoxide; Environmental science; Atmospheric sciences; China; Climatology; Meteorology; Seasonality; Geography; Geology; Chemistry; Mathematics; Statistics","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":[0.0003805462,0.0003731144,0.0002312221,0.000976121,0.0002639468,0.0004229869,0.0002885564,0.0002788656,0.0007003663],"category_scores_gemma":[0.0003946563,0.0001432936,0.0005333758,0.001487468,0.0002055252,0.0002857074,0.0003488351,0.000170279,0.0001473684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229524,"about_ca_system_score_gemma":0.001011847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1799198,"about_ca_topic_score_gemma":0.1997898,"domain_scores_codex":[0.9998708,0.000009812511,0.00001222746,0.00003947878,0.00003376284,0.00003387197],"domain_scores_gemma":[0.9995807,0.00002913309,0.00009437781,0.00002670289,0.0001863797,0.00008277304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009817206,0.00003362146,0.9805727,0.00006206935,0.0001796027,0.0002145179,0.000176853,0.006050819,0.003394838,0.0001828216,0.001696707,0.007337344],"study_design_scores_gemma":[0.000001870275,0.000008383206,0.9953564,0.000004787735,0.00002034322,0.0000251858,0.0001076857,0.003426837,0.0002995456,0.00002158288,0.0007197778,0.000007561147],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938846,0.0001661452,0.0002922261,0.0001255949,0.00001162667,0.000008866585,0.004567319,0.00004855766,0.0008949696],"genre_scores_gemma":[0.9943886,0.0001104044,0.0002012689,0.00003006663,0.000008496144,0.00001196853,0.004691813,0.000005587386,0.0005516386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1799198,"threshold_uncertainty_score":0.3577451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002806695722797132,"score_gpt":0.1724877256801574,"score_spread":0.1696810299573603,"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."}}