{"id":"W2134695704","doi":"10.1002/etc.2883","title":"Increase in mercury in Pacific yellowfin tuna","year":2015,"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":"","funders":"Fonds de recherche du Québec – Nature et technologies; National Science Foundation","keywords":"Mercury (programming language); Yellowfin tuna; Tuna; Environmental science; Fishery; Oceanography; Environmental chemistry; Biology; Fish <Actinopterygii>; Chemistry; Geology","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":[0.000166983,0.0001811324,0.0001667191,0.001312264,0.0005584738,0.0004448829,0.000190634,0.0003297535,0.001411967],"category_scores_gemma":[0.0004993234,0.0001093372,0.0002462739,0.001516133,0.0002955144,0.0002824396,0.0002907598,0.0002444595,0.0001851689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009293951,"about_ca_system_score_gemma":0.0004075492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08059099,"about_ca_topic_score_gemma":0.1042696,"domain_scores_codex":[0.9998873,0.000007673214,0.000009362783,0.00003898173,0.00003500811,0.00002147096],"domain_scores_gemma":[0.999707,0.00001708318,0.0001123118,0.00001420432,0.0001061745,0.00004321415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001274909,0.00001549663,0.9876772,0.00002977997,0.0000626033,0.0003376655,0.0003178169,0.00003713033,0.006316694,0.00002231251,0.0001596704,0.004896212],"study_design_scores_gemma":[9.643487e-7,0.00002298981,0.9986749,0.000002398752,0.00001240336,0.0001215868,0.0001988888,0.00002393815,0.0004151028,0.000008783549,0.000516637,0.000001314629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985219,0.0001870804,0.00002166689,0.0000558738,0.000005429388,0.000001881121,0.0003735438,0.000005697862,0.0008269178],"genre_scores_gemma":[0.9981558,0.0002063555,0.00008402716,0.00007014013,0.000006196226,0.000003814004,0.0003672361,0.000002837031,0.001103653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08059099,"threshold_uncertainty_score":0.1602438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205998047916199,"score_gpt":0.2284927807761952,"score_spread":0.2164328002970332,"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."}}