{"id":"W2327766428","doi":"10.1021/es300576p","title":"Methylmercury Cycling in High Arctic Wetland Ponds: Sources and Sinks","year":2012,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Methylmercury; Arctic; Wetland; Mercury (programming language); Sink (geography); Environmental science; Environmental chemistry; Temperate climate; Cycling; Deposition (geology); Ecology; Oceanography; Chemistry; Biology; Bioaccumulation; Geography; Geology; Sediment","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":[0.0001735324,0.000226454,0.000280024,0.0003947677,0.0008721619,0.0006740547,0.0002790419,0.0002497851,0.0006438657],"category_scores_gemma":[0.0001970305,0.000140112,0.0001786274,0.0005370462,0.0003656074,0.0003947022,0.0005677625,0.0001440735,0.00009174159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002509323,"about_ca_system_score_gemma":0.00124651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1680958,"about_ca_topic_score_gemma":0.2979096,"domain_scores_codex":[0.9998715,0.000008832281,0.00000468655,0.0000427046,0.00003598085,0.00003626042],"domain_scores_gemma":[0.9998504,0.00001700177,0.0000385277,0.000006509149,0.0000570383,0.00003048766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004901432,0.00008171189,0.6629391,0.0001424124,0.00007668856,0.0002642269,0.001121121,0.001976879,0.3133569,0.0003679345,0.0002236509,0.01895929],"study_design_scores_gemma":[0.00001264534,0.00009576512,0.9746218,0.000008026179,0.00003789648,0.00007850268,0.0008131407,0.006074942,0.01715534,0.0001845227,0.0009048862,0.0000125193],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988638,0.00007938846,0.0003123731,0.00001276888,8.31646e-7,0.000006648331,0.0001371117,0.00001404896,0.000572942],"genre_scores_gemma":[0.9984378,0.0001137375,0.0008681284,0.00001176487,0.000001185444,0.000008381584,0.0001389677,0.000004255657,0.0004156986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1680958,"threshold_uncertainty_score":0.3342348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008803962451913986,"score_gpt":0.2380709847013507,"score_spread":0.2292670222494367,"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."}}