{"id":"W1964307520","doi":"10.1080/15555270903143408","title":"Selenium Bioaccumulation in Freshwater Organisms and Antagonistic Effect against Mercury Assimilation","year":2009,"lang":"en","type":"article","venue":"Environmental Bioindicators","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"Ministry of Natural Resources","keywords":"Bioaccumulation; Mercury (programming language); Food chain; Selenium; Environmental chemistry; Aquatic ecosystem; Trophic level; Food web; Freshwater ecosystem; Periphyton; Perch; Biomagnification; Methylmercury; Assimilation (phonology); Zooplankton; Ecology; Biology; Ecosystem; Chemistry; Algae; Fishery; Fish <Actinopterygii>","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":[0.0001278917,0.0003268718,0.0001943777,0.0005145849,0.0005415368,0.0002556625,0.0001938653,0.0002146758,0.0008996585],"category_scores_gemma":[0.0001582845,0.0001400113,0.0001311495,0.0002983613,0.0003876311,0.0001343597,0.0003803145,0.0001442172,0.0001186401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005920392,"about_ca_system_score_gemma":0.0005426001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0201843,"about_ca_topic_score_gemma":0.06571381,"domain_scores_codex":[0.9998895,0.00001571782,0.000006540012,0.00002578173,0.00003512124,0.00002724057],"domain_scores_gemma":[0.999878,0.00001446589,0.00003531882,0.000007339983,0.00003752447,0.00002731294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001976267,0.00002554584,0.0331265,0.00006687572,0.00001773809,0.0002034587,0.0002226615,0.00008119187,0.9623165,0.00007336054,0.00003091103,0.003637621],"study_design_scores_gemma":[0.00002407867,0.00190995,0.6714066,0.00001891309,0.00006097138,0.0008816072,0.0008349011,0.0004950795,0.321584,0.0001884993,0.00256742,0.00002798887],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990727,0.0001923351,0.000163242,0.00001462909,0.000001097902,0.000002800648,0.00003620793,0.000005087881,0.0005118913],"genre_scores_gemma":[0.9976311,0.0002369593,0.000541069,0.00002314986,0.000001263432,0.00000589612,0.0001090949,0.000001449825,0.001450003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0201843,"threshold_uncertainty_score":0.04013366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005302475603074366,"score_gpt":0.2234856353174955,"score_spread":0.2181831597144211,"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."}}