{"id":"W2289551600","doi":"10.1021/acs.est.5b04921","title":"Photodemethylation of Methylmercury in Eastern Canadian Arctic Thaw Pond and Lake Ecosystems","year":2016,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Center for Northern Studies","funders":"Fonds de recherche du Québec – Nature et technologies; Aboriginal Affairs and Northern Development Canada; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Methylmercury; Ecosystem; Environmental chemistry; Arctic; Dissolved organic carbon; Environmental science; Permafrost; Thermokarst; Aquatic ecosystem; Lake ecosystem; Organic matter; Ecology; Chemistry; Bioaccumulation; Biology","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":[0.0002016697,0.0003064499,0.0002993833,0.0007353819,0.002049975,0.0008669925,0.0004501647,0.0002505381,0.0005853401],"category_scores_gemma":[0.0002971329,0.0002177189,0.0002237336,0.001156222,0.0004453073,0.0003619488,0.0006841619,0.0001931352,0.00006861942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01049328,"about_ca_system_score_gemma":0.005315792,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8480617,"about_ca_topic_score_gemma":0.9562256,"domain_scores_codex":[0.999769,0.00001168565,0.000009450499,0.0000558568,0.0000737943,0.00008025114],"domain_scores_gemma":[0.9996377,0.00001606818,0.00006998889,0.00001326478,0.0001821449,0.00008084263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005543553,0.00006550969,0.8627692,0.0001780996,0.000103673,0.0003313362,0.002064923,0.000519362,0.1151799,0.0001371211,0.0004943304,0.0176022],"study_design_scores_gemma":[0.000003366942,0.00002996941,0.9966198,0.000003018965,0.00001633576,0.00003448728,0.0004948112,0.0002324589,0.002017221,0.00001079493,0.0005325836,0.000005062328],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990085,0.0001389671,0.00003680193,0.00001627468,8.430587e-7,0.000006032776,0.0002055393,0.000007048337,0.000580128],"genre_scores_gemma":[0.9982448,0.0002298384,0.0002790828,0.00003120934,9.255923e-7,0.00001004257,0.0005744991,0.000003911917,0.0006257056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1519383,"threshold_uncertainty_score":0.3056662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009305160642777234,"score_gpt":0.2273194767046228,"score_spread":0.2180143160618455,"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."}}