{"id":"W2075082468","doi":"10.1289/ehp.7603","title":"Mercury, Food Webs, and Marine Mammals: Implications of Diet and Climate Change for Human Health","year":2005,"lang":"en","type":"article","venue":"Environmental Health Perspectives","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":231,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Pew Charitable Trusts","keywords":"Mercury (programming language); Methylmercury; Population; Climate change; Fishery; Environmental science; Pollutant; Gadus; Fishing; Ecosystem; Ecology; Biology; Environmental protection; Toxicology; Environmental health; Medicine; Bioaccumulation; 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":[0.0003022384,0.0001604094,0.0002702101,0.00004067446,0.0005535407,0.000009681014,0.00006609241,0.00003232126,0.0003241336],"category_scores_gemma":[0.000006951484,0.0001549159,0.00003821194,0.00005468828,0.0004234404,0.0002113618,0.0002223729,0.00007284011,0.00001143752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000311068,"about_ca_system_score_gemma":0.000006572638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002456411,"about_ca_topic_score_gemma":0.001081232,"domain_scores_codex":[0.9987823,0.00005701713,0.0003038559,0.0003510469,0.0001301069,0.0003756493],"domain_scores_gemma":[0.9993718,0.00004801562,0.0001997067,0.000159623,0.000002048791,0.0002188168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001433311,0.001129267,0.7427558,0.0003560237,0.00008683698,2.067606e-7,0.06970255,0.000006018331,0.002607546,0.01152641,0.003574855,0.1681112],"study_design_scores_gemma":[0.0005873392,0.001655728,0.9808506,0.00001850657,0.000008821494,0.000006440584,0.008227253,0.00001657634,0.0001089764,0.0007100065,0.007657235,0.0001524677],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750581,0.004623504,0.00005054795,0.01753983,0.00002113602,0.001163506,0.0004951478,0.00002640342,0.001021762],"genre_scores_gemma":[0.9879168,0.009139574,0.001783845,0.0008082613,0.00007395569,0.0001598055,0.00003346104,0.00001776214,0.00006649425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2380949,"threshold_uncertainty_score":0.6317286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04251726694591208,"score_gpt":0.3374854652215765,"score_spread":0.2949681982756644,"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."}}