{"id":"W2133263612","doi":"10.1016/j.scitotenv.2012.08.057","title":"Biomagnification of mercury through lake trout (Salvelinus namaycush) food webs of lakes with different physical, chemical and biological characteristics","year":2012,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":131,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Natural Resources and Forestry; Laurentian University; Environment and Climate Change Canada; University of Alberta; University of New Brunswick","funders":"Health Canada; Clean Air Regulatory Agenda; National Research Council Canada; Ministry of Natural Resources","keywords":"Biomagnification; Trophic level; Trout; Ecology; Benthic zone; Environmental science; δ15N; Food web; Zooplankton; Food chain; Mercury (programming language); Salvelinus; Ecosystem; Environmental chemistry; Stable isotope ratio; δ13C; Biology; Fishery; Chemistry; Fish <Actinopterygii>","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":[0.000155882,0.0001700237,0.0001726403,0.000765865,0.0006158357,0.0005061943,0.0002018167,0.0002467259,0.0008703886],"category_scores_gemma":[0.0002539123,0.0002159873,0.0002216219,0.0002964346,0.000445646,0.0005108241,0.0006133322,0.0001850655,0.0001014069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000830646,"about_ca_system_score_gemma":0.0003736918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02066403,"about_ca_topic_score_gemma":0.04631197,"domain_scores_codex":[0.9999267,0.00001007481,0.000004912052,0.00002697438,0.00001690965,0.00001448156],"domain_scores_gemma":[0.999823,0.00002582295,0.00006891508,0.000009629844,0.00002763954,0.0000450396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009312413,0.00008454393,0.5962341,0.00006132346,0.0002061969,0.0001749147,0.001730575,0.0005306349,0.3953181,0.0003565925,0.00007653723,0.004295164],"study_design_scores_gemma":[0.000005445389,0.00008786166,0.9955956,0.000001675279,0.00002767372,0.00006481077,0.0003131291,0.0008078645,0.002937661,0.00007304216,0.00008000604,0.000005292378],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998868,0.000007471501,0.00001685429,0.000003909595,1.316022e-7,5.38254e-7,0.00001810608,0.000001250246,0.00006513115],"genre_scores_gemma":[0.999548,0.00001504858,0.00008039332,0.000006515471,5.758512e-7,0.000002971368,0.00007153911,0.000001854904,0.0002730847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02066403,"threshold_uncertainty_score":0.04108751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100038369754076,"score_gpt":0.2320279687627587,"score_spread":0.211027585065218,"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."}}