{"id":"W2083444294","doi":"10.5194/acp-13-11339-2013","title":"The Atmospheric Mercury Network: measurement and initial examination of an ongoing atmospheric mercury record across North America","year":2013,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"U.S. Department of Agriculture; National Institute of Food and Agriculture; National Oceanic and Atmospheric Administration; U.S. Environmental Protection Agency","keywords":"Mercury (programming language); Environmental science; Elemental mercury; Atmospheric research; Air quality index; Meteorology; Geography; Computer science; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003236258,0.0003173921,0.0003265788,4.21413e-8,0.0006959329,0.0001058341,0.0002114265,0.00007961105,0.0006257079],"category_scores_gemma":[0.00005020188,0.000253246,0.00006533851,0.0004188172,0.0006943412,0.0004985121,0.000203094,0.0001900492,0.00003018807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009584278,"about_ca_system_score_gemma":0.00002289122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007663411,"about_ca_topic_score_gemma":0.00008096913,"domain_scores_codex":[0.998089,0.00009600776,0.0004051905,0.000420806,0.0004873289,0.0005016371],"domain_scores_gemma":[0.9989243,0.0001371363,0.0002983631,0.0003580561,0.00007883618,0.0002033257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002045515,0.00007919459,0.01882665,0.00004932052,0.00006706607,0.000001262318,0.001832507,0.00121049,0.004335075,0.000003866132,0.0006072417,0.9729668],"study_design_scores_gemma":[0.00132347,0.0003990399,0.8529562,0.0001077888,0.0001888771,0.00002554794,0.005946627,0.1033342,0.003219704,0.001145581,0.0300273,0.00132564],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950285,0.0005133994,0.0007731133,0.00007944516,0.00009097564,0.0002845447,0.000006399989,0.00004274535,0.003180863],"genre_scores_gemma":[0.9906499,0.0008715858,0.007497117,0.0001451818,0.0002197653,0.00007899124,0.00001666551,0.00002924577,0.0004914803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9716412,"threshold_uncertainty_score":0.999992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486792991559852,"score_gpt":0.2400776321620478,"score_spread":0.2252097022464493,"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."}}