{"id":"W2149229410","doi":"10.1016/j.cbpc.2013.02.004","title":"Effects of methylmercury on epigenetic markers in three model species: Mink, chicken and yellow perch","year":2013,"lang":"en","type":"article","venue":"Comparative Biochemistry and Physiology Part C Toxicology & Pharmacology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Dalhousie University; University of Ottawa; Ontario Genomics","funders":"National Institute of Environmental Health Sciences; National Oceanic and Atmospheric Administration; Natural Sciences and Engineering Research Council of Canada; School of Public Health, University of Michigan","keywords":"Mink; Methylmercury; Perch; DNA methylation; Biology; Epigenetics; Methylation; Juvenile; American mink; Zoology; DNA; Genetics; Fish <Actinopterygii>; Gene; Ecology; Fishery; Gene expression; Bioaccumulation","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":[0.0001165159,0.0002201267,0.0002142844,0.0002407285,0.0003397316,0.0002696028,0.0002217299,0.0004067564,0.001209532],"category_scores_gemma":[0.0002620706,0.0002322458,0.000188749,0.0001339276,0.0004982224,0.0002146758,0.0002593735,0.0004250047,0.0001474911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000509833,"about_ca_system_score_gemma":0.0002821508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009393774,"about_ca_topic_score_gemma":0.02742144,"domain_scores_codex":[0.9998958,0.00001878437,0.000007669313,0.00004205366,0.00001238293,0.00002328478],"domain_scores_gemma":[0.9997576,0.00005577201,0.00005970433,0.00002861751,0.00004344217,0.00005485988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003218234,0.00007625682,0.008786052,0.00004740704,0.00005436877,0.00005636032,0.0003002565,0.0001352118,0.9848756,0.00008634967,0.00005075804,0.002313247],"study_design_scores_gemma":[0.00009085781,0.004029403,0.2902502,0.00001245695,0.0002342046,0.0002580077,0.0009593071,0.001250883,0.7013387,0.0001422136,0.001399741,0.00003404381],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999505,0.0000879837,0.00009604877,0.00001719486,0.00000372008,0.000003470926,0.00007572887,0.000004612887,0.0002061215],"genre_scores_gemma":[0.9969703,0.0001259621,0.0004202366,0.00004027474,0.000001938048,0.00002133436,0.000231682,0.000009553061,0.002178769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009393774,"threshold_uncertainty_score":0.01867819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02983929903444835,"score_gpt":0.2997947989565984,"score_spread":0.26995549992215,"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."}}