{"id":"W1971013250","doi":"10.1021/es801635m","title":"Methylated Mercury Species in Marine Waters of the Canadian High and Sub Arctic","year":2008,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Trent University; University of Alberta; Environment and Climate Change Canada","funders":"University of Alberta; U.S. Environmental Protection Agency","keywords":"Water column; Mercury (programming language); Arctic; Oceanography; Bioaccumulation; Seawater; Bay; Environmental chemistry; Methylmercury; Biota; Environmental science; Archipelago; Chemistry; Geology; Ecology; 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":[0.0001954817,0.0004723692,0.0004003081,0.001944756,0.002039274,0.0007038061,0.000530528,0.0002977969,0.0005613198],"category_scores_gemma":[0.0004067741,0.0002646834,0.0002305349,0.002808442,0.0005386018,0.0001988171,0.0006267793,0.000222389,0.0001008461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007167894,"about_ca_system_score_gemma":0.005370889,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9483681,"about_ca_topic_score_gemma":0.9774767,"domain_scores_codex":[0.9996643,0.00001179875,0.00001332676,0.00007590726,0.0001619979,0.00007266291],"domain_scores_gemma":[0.9996033,0.00001798521,0.00005606923,0.000007472155,0.0002437795,0.00007125457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003969796,0.00002650726,0.8999075,0.0001674159,0.000177284,0.0002567566,0.002456816,0.000482669,0.07172585,0.0001912294,0.0004598325,0.02375107],"study_design_scores_gemma":[0.000003569243,0.0000314398,0.9949474,0.000008648402,0.0000334886,0.00008101293,0.0007373824,0.0002533962,0.002562135,0.00002241553,0.001307888,0.00001124388],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973749,0.0005264343,0.00008700011,0.00002137714,0.000003321549,0.000008073086,0.0009054876,0.000009282348,0.001064177],"genre_scores_gemma":[0.9968934,0.0005154548,0.0007193568,0.00004943467,0.000004169068,0.000009837988,0.0009332123,0.000005034268,0.0008700337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05163187,"threshold_uncertainty_score":0.1038718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00852673280083252,"score_gpt":0.1944772047483452,"score_spread":0.1859504719475127,"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."}}