{"id":"W2067032494","doi":"10.1007/s11356-012-1036-4","title":"Ecological and biological determinants of methylmercury accumulation in tropical coastal fish","year":2012,"lang":"en","type":"article","venue":"Environmental Science and Pollution Research","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research Council Canada; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Bay; Methylmercury; Predatory fish; Eutrophication; Environmental science; Mercury (programming language); Fishery; Environmental chemistry; Bioaccumulation; Ecology; Biology; Fish <Actinopterygii>; Chemistry; Oceanography; Nutrient","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002004467,0.000152195,0.0001330332,0.0005941287,0.0003553163,0.0003432306,0.0002005392,0.0002394751,0.001427365],"category_scores_gemma":[0.0005562853,0.0002526211,0.000199661,0.0005126577,0.0005404529,0.0002901354,0.0003804501,0.0002530155,0.0001601706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006509378,"about_ca_system_score_gemma":0.0005510771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02614389,"about_ca_topic_score_gemma":0.0479608,"domain_scores_codex":[0.9999049,0.00001305425,0.000007628693,0.00002688052,0.00001662958,0.00003091784],"domain_scores_gemma":[0.9994761,0.00009399851,0.0002063725,0.00002533446,0.00007610453,0.00012211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001132017,0.0001122123,0.8784838,0.00003279746,0.00007598996,0.0002695993,0.0006553371,0.0002428061,0.1167988,0.0001286652,0.0000360727,0.002031874],"study_design_scores_gemma":[0.00000267746,0.00008180018,0.998004,9.833457e-7,0.00001040036,0.00005522813,0.000313965,0.00008932663,0.001386978,0.00001995859,0.00003205324,0.00000264713],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998043,0.00001639514,0.00001112052,0.000007904626,2.451708e-7,9.962178e-7,0.00003848076,4.231164e-7,0.0001201596],"genre_scores_gemma":[0.9995285,0.00004625804,0.00003747345,0.000007023576,9.130113e-7,0.00000311551,0.00004860045,8.529327e-7,0.0003273195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02614389,"threshold_uncertainty_score":0.05198342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1292319367714303,"score_gpt":0.4000943570764699,"score_spread":0.2708624203050396,"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."}}