{"id":"W4417118011","doi":"10.5194/acp-25-17907-2025","title":"Decadal changes in atmospheric ammonia and dry deposition across China inferred from space-ground measurements and model simulations","year":2025,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Natural Science Foundation of Jiangsu Province for Distinguished Young Scholars; “333 Project” of Jiangsu Province; National Key Research and Development Program of China; Environment and Climate Change Canada; Government of Jiangsu Province; China Meteorological Administration; National Natural Science Foundation of China; European Centre for Medium-Range Weather Forecasts; National Bureau of Statistics of China","keywords":"Deposition (geology); Ammonia; Particulates; Ecosystem; Nitrogen; Seasonality; Precipitation","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":[0.0004472811,0.0006067592,0.0003219496,0.0005143277,0.0003588358,0.0005706439,0.0007311096,0.0005923722,0.0008613495],"category_scores_gemma":[0.0004971189,0.000365688,0.001138068,0.0008236678,0.0003339572,0.0005284723,0.000294949,0.000333805,0.0001308131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001567624,"about_ca_system_score_gemma":0.001056579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1731244,"about_ca_topic_score_gemma":0.08896401,"domain_scores_codex":[0.9998949,0.00001742673,0.000008222019,0.00004366067,0.00001073302,0.0000250659],"domain_scores_gemma":[0.9998412,0.00003658478,0.00002631939,0.00002481799,0.00003982782,0.00003126333],"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":[0.0001732881,0.0001338226,0.2028793,0.00006694032,0.0004014704,0.0002508349,0.00007790024,0.7870045,0.002698844,0.0007682439,0.001160276,0.004384594],"study_design_scores_gemma":[0.00006075496,0.00002515644,0.09008028,0.000007393673,0.0000845903,0.00001847746,0.00004099423,0.9085608,0.0005245145,0.0002034341,0.0003711364,0.00002247267],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976237,0.00006799874,0.0005675504,0.00005888213,0.00001106117,0.000005204119,0.001092187,0.0000625447,0.0005107565],"genre_scores_gemma":[0.9982529,0.00004900822,0.000371214,0.00001403295,0.000004624743,0.000008471619,0.001128665,0.000008802457,0.000162233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1731244,"threshold_uncertainty_score":0.3442335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01341893015384807,"score_gpt":0.2377484255078142,"score_spread":0.2243294953539662,"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."}}