{"id":"W339188483","doi":"","title":"Sedimentary Records of Mercury and Organic Matter in Canadian Lakes; Relationship between Climate Change and Contaminants","year":2010,"lang":"en","type":"article","venue":"EGUGA","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sedimentary depositional environment; Sedimentary rock; Arctic; Sedimentary organic matter; Climate change; Mercury (programming language); Organic matter; Biogenic silica; Geology; Geologic record; Sediment; Kerogen; Environmental science; Oceanography; Physical geography; Geochemistry; Ecology; Source rock; Paleontology; Geography; Structural basin","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000312965,0.0001978608,0.0001883099,0.002303643,0.001778774,0.0008748524,0.0004974818,0.0002388307,0.0006311833],"category_scores_gemma":[0.00103661,0.0001793396,0.0001796259,0.005171934,0.0006552675,0.000287321,0.0005451051,0.0002239938,0.00008062994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009651342,"about_ca_system_score_gemma":0.007129698,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9810507,"about_ca_topic_score_gemma":0.9932027,"domain_scores_codex":[0.9997756,0.00001182818,0.0000150955,0.00004455548,0.00009315732,0.00005968815],"domain_scores_gemma":[0.9989749,0.00006063145,0.0002398345,0.0000273423,0.0005715074,0.0001258324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006214352,0.00000929071,0.9907702,0.00003867417,0.00007800842,0.00007974145,0.0005819825,0.0002616951,0.001680279,0.00007806916,0.0003507983,0.006009206],"study_design_scores_gemma":[7.440838e-7,0.000002968229,0.9990578,0.000003493774,0.000008418104,0.00001673428,0.0001720461,0.00009308822,0.0001184432,0.000006595963,0.0005168021,0.000002912306],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957767,0.0007486055,0.0000637759,0.00008885859,0.000003249751,0.000005022624,0.002312215,0.00001133701,0.000990289],"genre_scores_gemma":[0.9978969,0.000404702,0.0001684,0.00002441643,0.000002780964,0.000003253137,0.001099405,0.000002465826,0.0003976552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01894933,"threshold_uncertainty_score":0.07002574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02940826476598665,"score_gpt":0.2592625468196705,"score_spread":0.2298542820536838,"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."}}