{"id":"W2117602099","doi":"10.1016/j.apgeochem.2007.12.020","title":"Assessing sulfate and carbon controls on net methylmercury production in peatlands: An in situ mesocosm approach","year":2008,"lang":"en","type":"article","venue":"Applied Geochemistry","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":122,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Methylmercury; Mesocosm; Peat; Environmental chemistry; Chemistry; Organic matter; Sulfate; Dissolved organic carbon; Total organic carbon; Ecology; Bioaccumulation; Nutrient; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002934262,0.0001584166,0.0002089366,0.00003239094,0.00008404422,0.00002203894,0.00007307609,0.00008527708,0.00001961226],"category_scores_gemma":[0.00003503033,0.0001490661,0.00001484342,0.0001857334,0.0001569519,0.0001400977,0.00005087963,0.0001995263,0.000003799151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009174221,"about_ca_system_score_gemma":0.00001114121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001371253,"about_ca_topic_score_gemma":0.00005205208,"domain_scores_codex":[0.998919,0.00003140176,0.0001984846,0.0004049081,0.0001964066,0.0002498671],"domain_scores_gemma":[0.9996318,0.00003257937,0.00006694334,0.000190114,0.0000040459,0.00007450323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004763935,0.0001672179,0.07871179,0.00002074981,0.000007142965,0.00000896428,0.001900312,0.0003131127,0.9150102,0.00001112552,0.0001446005,0.003657184],"study_design_scores_gemma":[0.001491074,0.00003132616,0.5057939,0.00002585896,0.00001464922,0.00003781388,0.003179984,0.0003184261,0.4879609,0.0004898459,0.0002236883,0.0004324875],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.932745,0.00008567498,0.000005404534,0.00007621699,0.00001989158,0.0002143765,9.422919e-7,0.00002419675,0.0668283],"genre_scores_gemma":[0.9993225,0.00006303246,0.0002475296,0.00007061699,0.00005391274,0.00008008099,0.00004038196,0.000009593768,0.0001123422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4270822,"threshold_uncertainty_score":0.6078737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02431839669103097,"score_gpt":0.261145625998419,"score_spread":0.236827229307388,"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."}}