{"id":"W2021805224","doi":"10.1021/es0306009","title":"Historical Variations in the Stable Isotope Composition of Mercury in Arctic Lake Sediments","year":2004,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Environment and Climate Change Canada","funders":"","keywords":"Sediment; Delta; Arctic; Mercury (programming language); Anoxic waters; Fractionation; Stable isotope ratio; Environmental chemistry; Geology; Chemistry; Mineralogy; Chemical composition; Isotope; Manganese; Oceanography; Paleontology","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":[0.0005139359,0.0001021118,0.0001413513,0.0002598639,0.0001771933,0.000008656122,0.0004432646,0.00006294568,0.0003484801],"category_scores_gemma":[0.00003324733,0.00008158293,0.0000230843,0.001402112,0.001110108,0.0003144153,0.00021994,0.0001758275,0.00008909855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001510822,"about_ca_system_score_gemma":0.00001697433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000554736,"about_ca_topic_score_gemma":0.0003783943,"domain_scores_codex":[0.9986667,0.00003226406,0.0002740064,0.0002740384,0.0004344066,0.0003185918],"domain_scores_gemma":[0.9996033,0.00002557426,0.00009199712,0.000241278,0.000001731578,0.00003613867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006983162,0.0006009281,0.7831846,0.000002749398,0.000002582161,0.000009086414,0.001924672,0.001721485,0.2087114,0.002249196,0.00004678653,0.001539467],"study_design_scores_gemma":[0.0007026893,0.0001702128,0.9688014,0.00001977644,0.000008366964,0.00002541417,0.001472238,0.00005220775,0.01774084,0.007613152,0.003222628,0.0001711248],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950874,0.00006705401,0.0002739767,0.00217777,0.00006761892,0.0002810842,0.000004596981,0.00001542691,0.002025062],"genre_scores_gemma":[0.9989953,0.00004145008,0.0007208885,0.0001488055,0.000004623233,0.00004372698,0.000002499148,0.000003885566,0.00003883003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1909706,"threshold_uncertainty_score":0.409024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01004909113440451,"score_gpt":0.2332891368136015,"score_spread":0.223240045679197,"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."}}