{"id":"W2057617072","doi":"10.1016/j.marpolbul.2006.08.046","title":"Temporal trends of mercury in marine biota of west and northwest Greenland","year":2006,"lang":"en","type":"article","venue":"Marine Pollution Bulletin","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"Miljøstyrelsen; University of Saskatchewan; Statens Naturvidenskabelige Forskningsrad","keywords":"Biota; Mercury (programming language); Oceanography; Groenlandia; Environmental science; Geology; Physical geography; Geography; Ecology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002595209,0.0001095063,0.0002461496,0.0001669589,0.00002713632,0.000003773046,0.0001190399,0.0000661455,0.01308186],"category_scores_gemma":[0.00002011911,0.0001041831,0.00004449554,0.0003879626,0.0002833561,0.00002861301,0.0004093717,0.00007678419,0.00005541564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005763146,"about_ca_system_score_gemma":0.000004878848,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07624025,"about_ca_topic_score_gemma":0.08027355,"domain_scores_codex":[0.9989946,0.00006397077,0.0003971714,0.0002167857,0.0001488837,0.000178545],"domain_scores_gemma":[0.9995821,0.00002521839,0.0001655861,0.000189464,0.000007262405,0.00003041524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002829493,0.0001406786,0.9872726,0.000006971223,0.000005928785,0.000006588618,0.00001990044,0.000200771,0.0009449163,0.0001326347,0.0009318597,0.0103089],"study_design_scores_gemma":[0.0005110924,0.0000738377,0.9810943,0.000003056984,0.00001550888,0.000009624334,0.00001036863,0.0001702007,0.0004841192,0.0001879875,0.01734617,0.00009374004],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707242,0.00001243729,0.000009540961,0.001808138,0.00002728984,0.00005957748,0.00001361885,0.000008195218,0.02733695],"genre_scores_gemma":[0.9957333,0.00001624649,0.001115417,0.00005636087,0.00002003917,0.000004991424,0.00004965522,0.000007552661,0.002996389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0250091,"threshold_uncertainty_score":0.9878203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004187554963997191,"score_gpt":0.1963860694289566,"score_spread":0.1921985144649594,"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."}}