{"id":"W4286687397","doi":"10.1016/j.scitotenv.2022.157445","title":"Arctic methylmercury cycling","year":2022,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wildlife Conservation Society Canada; Laurentian University; Environment and Climate Change Canada; University of Manitoba","funders":"Vetenskapsrådet; AXA Research Fund; Environment and Climate Change Canada; Svenska Forskningsrådet Formas","keywords":"Methylmercury; Arctic; Environmental chemistry; Bioaccumulation; Biogeochemical cycle; Environmental science; Biomagnification; Thermokarst; Permafrost; Biota; Arctic vegetation; Ecology; Ecosystem; Biogeochemistry; Mercury (programming language); Arctic ecology; Oceanography; Tundra; Chemistry; Geology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004162496,0.0007986538,0.0004391895,0.001068619,0.001060244,0.001301891,0.0007452814,0.0007991132,0.005892326],"category_scores_gemma":[0.0005162341,0.0002116979,0.0004824444,0.001362791,0.0002034095,0.0008834671,0.001238551,0.0005766783,0.002880933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001565425,"about_ca_system_score_gemma":0.001289147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03626605,"about_ca_topic_score_gemma":0.03198149,"domain_scores_codex":[0.9995863,0.00005350439,0.00002629815,0.000140245,0.0001285688,0.00006508252],"domain_scores_gemma":[0.999727,0.00001634464,0.00004479104,0.00001467717,0.0001668854,0.00003034617],"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":[0.0008720371,0.00008991969,0.06324877,0.007776222,0.0008051311,0.002523481,0.001522924,0.005622664,0.282553,0.02240928,0.05921667,0.5533599],"study_design_scores_gemma":[0.000025732,0.0001921839,0.05366554,0.0007656065,0.0005283373,0.001574308,0.0008371185,0.003265443,0.06540629,0.007528891,0.8661031,0.0001075303],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3244906,0.366711,0.01872822,0.005861125,0.002414561,0.0001575768,0.01959552,0.001964434,0.260077],"genre_scores_gemma":[0.7220249,0.1893632,0.01072612,0.002089448,0.0007940811,0.00009848778,0.01341266,0.0004348117,0.06105626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03626605,"threshold_uncertainty_score":0.07210994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0167153888756377,"score_gpt":0.2393958909597597,"score_spread":0.222680502084122,"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."}}