{"id":"W4389109611","doi":"10.1021/acs.est.3c05585","title":"Enhanced Bioaccumulation and Transfer of Monomethylmercury through Periphytic Biofilms in Benthic Food Webs of a River Affected by Run-of-River Dams","year":2023,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Hydro-Québec; Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Hydro-Québec; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Periphyton; Bioaccumulation; Biomagnification; Trophic level; Benthic zone; Environmental science; Aquatic ecosystem; River ecosystem; Ecology; Hydrology (agriculture); Mercury (programming language); Food web; Algae; Environmental chemistry; Habitat; 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":[0.0000970668,0.0001617949,0.0001236785,0.0002060439,0.0003826215,0.0003075797,0.0001432938,0.0001780332,0.0004587688],"category_scores_gemma":[0.0001672472,0.0001433524,0.0001350511,0.0001986667,0.0001932296,0.0001480072,0.0001827692,0.0001408893,0.00006885224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009516657,"about_ca_system_score_gemma":0.0005443803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2491898,"about_ca_topic_score_gemma":0.4323788,"domain_scores_codex":[0.9999456,0.000007475698,0.000002412567,0.00001860956,0.000009298422,0.0000165704],"domain_scores_gemma":[0.9999141,0.00001149232,0.00001986499,0.000003692376,0.0000273393,0.00002357654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002130661,0.00007203283,0.7290739,0.00005597487,0.00005961375,0.0003903161,0.001543385,0.001240264,0.2587867,0.00005043427,0.0001072754,0.008407071],"study_design_scores_gemma":[0.000001088148,0.00005866946,0.9968923,0.00000154921,0.000009452342,0.00003113464,0.0003421044,0.0008225341,0.001747556,0.000009302124,0.0000813493,0.000002957699],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998509,0.00001047287,0.00003363362,0.000002621332,1.276804e-7,9.029237e-7,0.00003499885,0.000001132019,0.00006525322],"genre_scores_gemma":[0.9994512,0.00002165131,0.0001429211,0.000004729605,1.952093e-7,0.000001958841,0.00007567029,7.421546e-7,0.0003008219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2491898,"threshold_uncertainty_score":0.4954787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01302303151298796,"score_gpt":0.2554588798082421,"score_spread":0.2424358482952542,"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."}}