{"id":"W4283392398","doi":"10.3390/atmos13071012","title":"Seasonal Aerosol Acidity, Liquid Water Content and Their Impact on Fine Urban Aerosol in SE Canada","year":2022,"lang":"en","type":"article","venue":"Atmosphere","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; Environment and Climate Change Canada","funders":"","keywords":"Aerosol; Environmental science; Nitrate; Ammonium; Flux (metallurgy); Sulfate; Atmospheric sciences; Deposition (geology); Air quality index; Environmental chemistry; Ammonium sulfate; NOx; Ammonium nitrate; Meteorology; Chemistry; Combustion; Geography; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000151442,0.0002984179,0.0002649844,0.0007786605,0.001615393,0.001161969,0.0004433374,0.0002316566,0.001447786],"category_scores_gemma":[0.0004227069,0.0001926991,0.0003051097,0.001731961,0.0005230685,0.0003030069,0.0004976213,0.0002262082,0.0001658097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02125595,"about_ca_system_score_gemma":0.0168241,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957064,"about_ca_topic_score_gemma":0.9983688,"domain_scores_codex":[0.9997343,0.00001156008,0.000009398635,0.00003871471,0.00009863056,0.0001073327],"domain_scores_gemma":[0.999543,0.00002547615,0.00005390776,0.00001193925,0.0002686458,0.00009708655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001357267,0.00002637344,0.9805824,0.00006437663,0.00008339747,0.0004197799,0.00107913,0.001619687,0.005858561,0.0003851258,0.00123565,0.008509654],"study_design_scores_gemma":[0.000003143578,0.000009635057,0.9958259,0.000007871722,0.00001681235,0.00003293752,0.00123539,0.0008153911,0.000416692,0.00002993909,0.001596064,0.00001023398],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950445,0.0003453562,0.0001209475,0.0001302205,0.000005357921,0.00001682221,0.001285514,0.0000177617,0.003033584],"genre_scores_gemma":[0.9976946,0.0002100228,0.0001367905,0.00002612653,0.000001936999,0.000003971683,0.0005911611,0.000006820806,0.001328656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02125595,"threshold_uncertainty_score":0.1542234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01624974050825761,"score_gpt":0.2010296240267952,"score_spread":0.1847798835185376,"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."}}