{"id":"W2954485418","doi":"10.5194/acp-20-721-2020","title":"Decoding long-term trends in the wet deposition of sulfate, nitrate, and ammonium after reducing the perturbation from climate anomalies","year":2020,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Key Research and Development Program of China; Environment and Climate Change Canada","keywords":"Deposition (geology); Nitrate; Environmental science; NOx; Ammonium; Atmospheric sciences; Sulfate; Environmental chemistry; Ammonium nitrate; Climatology; Chemistry; Combustion; Geology; Structural basin","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002195783,0.0004282392,0.0002199639,0.001101185,0.0003251608,0.0004498691,0.0002180698,0.0002309441,0.0006752595],"category_scores_gemma":[0.0003942632,0.0001091206,0.0003400325,0.001425922,0.0001070842,0.0001691765,0.0002097859,0.0001552624,0.0002803016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009401087,"about_ca_system_score_gemma":0.001448132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3783371,"about_ca_topic_score_gemma":0.6115183,"domain_scores_codex":[0.9999057,0.000004986,0.000005289974,0.00002760531,0.00002992234,0.00002649374],"domain_scores_gemma":[0.9997904,0.00001848809,0.00002995903,0.00001741854,0.0001240652,0.00001975487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005663987,0.0001677813,0.7328609,0.0002099158,0.0005506745,0.000678446,0.0003514744,0.03907849,0.1016376,0.0003378378,0.005815087,0.1177453],"study_design_scores_gemma":[0.00001125152,0.00003052495,0.928009,0.000008020297,0.00004410432,0.0000412597,0.0001978248,0.06166963,0.006935289,0.00007131934,0.002966508,0.00001541905],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832988,0.0002071488,0.004730331,0.00004993934,0.00002323254,0.00001888083,0.009990935,0.0004083351,0.001272348],"genre_scores_gemma":[0.963856,0.0001754396,0.008024821,0.00002428332,0.00001783165,0.00002765684,0.02618399,0.00005669438,0.001633322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3783371,"threshold_uncertainty_score":0.7522699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01081423402048141,"score_gpt":0.2035572714715679,"score_spread":0.1927430374510865,"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."}}