{"id":"W2025458598","doi":"10.1002/etc.95","title":"Mercury concentrations in landlocked Arctic char (<i>Salvelinus alpinus</i>) from the Canadian Arctic. Part I: Insights from trophic relationships in 18 lakes","year":2009,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Waterloo; Environment and Climate Change Canada","funders":"Österreichischen Akademie der Wissenschaften; Canadian Foundation for Climate and Atmospheric Sciences; Parks Canada","keywords":"Trophic level; Biomagnification; Arctic char; Zooplankton; Benthic zone; Arctic; Periphyton; Food web; Hydropsychidae; Ecology; Environmental science; Food chain; Mercury (programming language); Salvelinus; Environmental chemistry; Oceanography; Biology; Chemistry; Fishery; Nutrient; Geology; Trout","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009809498,0.0001738959,0.0001801941,0.00001609579,0.0003436992,0.00002241282,0.0001392102,0.0001932997,0.003151333],"category_scores_gemma":[0.00007030149,0.0001495912,0.00003166738,0.00009525058,0.0004306853,0.0001248112,0.00004335889,0.0004291962,0.0001015631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004711053,"about_ca_system_score_gemma":0.0000307161,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01131719,"about_ca_topic_score_gemma":0.1380687,"domain_scores_codex":[0.9988614,0.0001112847,0.0002732094,0.0003287212,0.0001391181,0.0002862103],"domain_scores_gemma":[0.9993684,0.000197501,0.00006876913,0.0001961683,0.000001362988,0.0001678558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000023186,0.0001276055,0.9050472,0.000001862431,0.00001930142,0.00003508333,0.002352978,0.00009870542,0.09094425,0.0000205907,0.0008353628,0.0004938973],"study_design_scores_gemma":[0.0006224971,0.00002632067,0.9875918,0.0000218049,0.00002067591,0.000006175294,0.0008873752,0.00006824899,0.004101462,0.002210879,0.004263049,0.0001797382],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994535,0.000839184,0.000001145549,0.002470393,0.00006105337,0.0001699849,0.00009050182,0.000009882356,0.00182287],"genre_scores_gemma":[0.9977878,0.0003526522,0.00003902871,0.001294921,0.00007693622,0.00002957664,0.0002012455,0.000007000408,0.0002108692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1267515,"threshold_uncertainty_score":0.9977599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01793526915037088,"score_gpt":0.2194423782737321,"score_spread":0.2015071091233613,"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."}}