{"id":"W2966300283","doi":"10.1038/s41586-019-1468-9","title":"Climate change and overfishing increase neurotoxicant in marine predators","year":2019,"lang":"en","type":"article","venue":"Nature","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":251,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada","funders":"Northwestern University; U.S. Environmental Protection Agency","keywords":"Overfishing; Methylmercury; Tuna; Gadus; Yellowfin tuna; Swordfish; Marine ecosystem; Apex predator; Fishery; Population; Environmental science; Mercury (programming language); Ecosystem; Biomagnification; Ecology; Biology; Bioaccumulation; Fishing; Fish <Actinopterygii>","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001124293,0.00006472295,0.00007703299,0.0000199866,0.00002901469,0.00001465726,0.00005313673,0.0001393041,0.0007344563],"category_scores_gemma":[0.0000371875,0.00005264361,0.00001046825,0.0001079032,0.00002505421,0.00021793,0.0002320252,0.0004121308,0.00008523132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002230666,"about_ca_system_score_gemma":0.000001223928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001569033,"about_ca_topic_score_gemma":0.0001387735,"domain_scores_codex":[0.999516,0.00001939157,0.0000639896,0.0001389776,0.000117357,0.000144359],"domain_scores_gemma":[0.99981,0.00002314605,0.00002527339,0.00008965381,0.000001707427,0.00005022419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001171112,0.00001017175,0.9918606,0.000008997768,0.00000105629,0.00000439753,0.0002959636,9.817491e-7,0.002164764,0.00009327674,0.0004925329,0.005055566],"study_design_scores_gemma":[0.0002138348,0.00002018687,0.993584,0.0000127104,0.000002134659,0.000003481875,0.00006054205,0.00005754096,0.0004649669,0.00008012753,0.00543317,0.00006731892],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854188,0.00006666036,5.816783e-8,0.00042483,0.00008514013,0.0002190685,0.000009639304,0.00001313656,0.01376267],"genre_scores_gemma":[0.9978497,0.000139993,0.00005330053,0.001790687,0.00002385019,0.00001057485,0.000004023718,0.000004887678,0.000122975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01363969,"threshold_uncertainty_score":0.8041782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166935512414509,"score_gpt":0.2484757724728274,"score_spread":0.2368064173486823,"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."}}