{"id":"W2317765497","doi":"10.1021/es025944y","title":"Continuous Analysis of Dissolved Gaseous Mercury (DGM) and Mercury Flux in Two Freshwater Lakes in Kejimkujik Park, Nova Scotia:  Evaluating Mercury Flux Models with Quantitative Data","year":2003,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Ottawa; Geological Survey of Canada; Natural Resources Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mercury (programming language); Nova scotia; Environmental science; Flux (metallurgy); Wind speed; Atmospheric sciences; Humidity; Dissolved organic carbon; Relative humidity; Wind direction; Meteorology; Chemistry; Environmental chemistry; Oceanography; Geology; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001878748,0.000384757,0.0007567478,0.001006114,0.0002230615,0.00003824544,0.0008792721,0.0001216555,0.001197558],"category_scores_gemma":[0.0002415187,0.0003201929,0.00005243508,0.003485532,0.005076982,0.001151741,0.0008958607,0.0003617622,0.00005751674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003332853,"about_ca_system_score_gemma":0.00004414123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001323581,"about_ca_topic_score_gemma":0.01748843,"domain_scores_codex":[0.9961526,0.0001826268,0.0007054719,0.001251114,0.0008674515,0.0008407779],"domain_scores_gemma":[0.9984446,0.0001516611,0.000316962,0.0009270726,0.00001068868,0.00014907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004927562,0.0003086571,0.7042634,0.000006849003,0.0001141629,0.00003597314,0.002368531,0.01206,0.2763955,0.0003900668,0.00003358434,0.003974013],"study_design_scores_gemma":[0.00614662,0.001880606,0.6705515,0.0002684292,0.001401605,0.0001794482,0.04754811,0.120965,0.1397047,0.007619744,0.0009471133,0.002787161],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964712,0.0005389288,0.0007805024,0.0002526528,0.00005483108,0.0005207597,0.0001430362,0.00003619834,0.00120193],"genre_scores_gemma":[0.99027,0.00009369801,0.009349614,0.00007936741,0.000003268172,0.00002628363,0.00006268299,0.00002064008,0.00009448142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1366907,"threshold_uncertainty_score":0.999925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03888003485955147,"score_gpt":0.31809048259813,"score_spread":0.2792104477385785,"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."}}