{"id":"W2203735225","doi":"10.1016/j.scitotenv.2015.12.030","title":"Mercury and cadmium in ringed seals in the Canadian Arctic: Influence of location and diet","year":2016,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"Royal Military College of Canada; Fisheries and Oceans Canada; Environment and Climate Change Canada; University of Manitoba; University of Windsor; Memorial University of Newfoundland","funders":"Northern Contaminants Program; Aboriginal Affairs and Northern Development Canada; Fisheries and Oceans Canada; Environment Canada; ArcticNet","keywords":"Biomagnification; Mercury (programming language); Arctic; Bay; Trophic level; Cadmium; Environmental science; Predation; Oceanography; Ecology; Fishery; Environmental chemistry; Chemistry; Biology; Geology","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":[0.0003252268,0.0002717328,0.0004334928,0.0007320034,0.002133599,0.000782495,0.000455718,0.0004836709,0.001159936],"category_scores_gemma":[0.0006484119,0.000369621,0.0004001572,0.001152676,0.0007499998,0.0003046377,0.0003908944,0.0003102669,0.0001795653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005982675,"about_ca_system_score_gemma":0.005088993,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9564707,"about_ca_topic_score_gemma":0.9799039,"domain_scores_codex":[0.9997874,0.00001637096,0.000008055162,0.00004991645,0.00005731246,0.00008093566],"domain_scores_gemma":[0.9995851,0.00003200434,0.00007550179,0.00001820751,0.0001900993,0.00009910364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000830861,0.00005128144,0.9905632,0.00002657758,0.0001218665,0.0001312793,0.001672865,0.0001361416,0.003457991,0.00005771371,0.0002451985,0.002705081],"study_design_scores_gemma":[0.00000249039,0.00004498199,0.9980474,0.000005044905,0.00002873101,0.00004389216,0.001249996,0.00006793717,0.0001817743,0.00001152,0.0003110745,0.000005151899],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991763,0.0001557298,0.00002084338,0.0000285026,0.000003149165,0.000002236276,0.0002855888,0.000001449812,0.0003261636],"genre_scores_gemma":[0.9979355,0.0002113302,0.00007549474,0.00002935287,0.000002150887,0.000003251868,0.000295262,0.000002842904,0.001444785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04352927,"threshold_uncertainty_score":0.0875712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01121678706600597,"score_gpt":0.2254612335571666,"score_spread":0.2142444464911606,"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."}}