{"id":"W2015406624","doi":"10.3390/atmos5030635","title":"A Survey of Mercury in Air and Precipitation across Canada: Patterns and Trends","year":2014,"lang":"en","type":"article","venue":"Atmosphere","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Windsor; University of Alberta; Environment and Climate Change Canada","funders":"Aboriginal Affairs and Northern Development Canada; Government of Canada; Manitoba Hydro","keywords":"Mercury (programming language); Environmental science; Atmospheric sciences; Precipitation; Arctic; MERCURE; Environmental chemistry; Elemental mercury; Aerosol; Particulates; Atmospheric chemistry; Latitude; Deposition (geology); Climatology; Oceanography; Meteorology; Chemistry; Geology; Ozone; Geography; Analytical Chemistry (journal)","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":[0.0002854099,0.0003329164,0.000239593,0.002812046,0.001265036,0.000780098,0.0005130109,0.0001901381,0.0007942167],"category_scores_gemma":[0.0004735042,0.0001796574,0.0002512438,0.008115364,0.0002983544,0.0002207463,0.0004476443,0.0003014837,0.0001469712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01032294,"about_ca_system_score_gemma":0.01200224,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9906872,"about_ca_topic_score_gemma":0.9938743,"domain_scores_codex":[0.9996167,0.00001347079,0.0000210046,0.00006913202,0.0002154139,0.00006424588],"domain_scores_gemma":[0.998847,0.00003529693,0.0001328828,0.00002027269,0.0008227546,0.0001416741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006534714,0.00002740202,0.9614317,0.0001583865,0.0001318502,0.00006443945,0.0006297578,0.0002834457,0.001989569,0.00009672843,0.002319182,0.0328021],"study_design_scores_gemma":[0.000001162022,0.000009359832,0.9971082,0.00000885019,0.00001218855,0.00002015125,0.0001736157,0.0001268081,0.0001972001,0.000006405779,0.002331754,0.000004308165],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9596393,0.003762865,0.0008018257,0.0003565254,0.00001860459,0.00006131255,0.03093987,0.0001276208,0.004292134],"genre_scores_gemma":[0.9785041,0.00295082,0.001697735,0.0001624219,0.00001300249,0.00003764164,0.01290045,0.00001799544,0.003715902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01032294,"threshold_uncertainty_score":0.07489854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01300693556803632,"score_gpt":0.2530154328901257,"score_spread":0.2400084973220894,"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."}}