{"id":"W4210822667","doi":"10.1016/j.scitotenv.2022.153715","title":"Climate change and mercury in the Arctic: Abiotic interactions","year":2022,"lang":"en","type":"review","venue":"The Science of The Total Environment","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of British Columbia; McGill University; Environment and Climate Change Canada; Geological Survey of Canada; Carleton University; Natural Resources Canada","funders":"Ulkoministeriö; Environment and Climate Change Canada; Miljøstyrelsen; Aarhus Universitet","keywords":"Permafrost; Biogeochemical cycle; Environmental science; Climate change; Arctic; Thermokarst; Cryosphere; Biogeochemistry; Ecosystem; Global warming; Cycling; Arctic geoengineering; Mercury (programming language); Oceanography; Physical geography; Ecology; Sea ice; Arctic ice pack; Geology; Antarctic sea ice; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000420644,0.0005121991,0.0004600977,0.0004012444,0.0007274564,0.001327565,0.0002239096,0.000324767,0.00180221],"category_scores_gemma":[0.0005864548,0.000161594,0.0006075479,0.001016526,0.0004800549,0.0003798487,0.000968331,0.0004590731,0.0002486164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000608829,"about_ca_system_score_gemma":0.0008301673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0225179,"about_ca_topic_score_gemma":0.03557217,"domain_scores_codex":[0.9997737,0.00008302939,0.0000144444,0.00004867853,0.00003911586,0.00004111711],"domain_scores_gemma":[0.9996883,0.00007101658,0.00008967934,0.0000130193,0.00007252515,0.00006545057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004426861,0.0001687377,0.869113,0.002265811,0.003675974,0.001055364,0.001825732,0.003124952,0.01063739,0.006361507,0.005546859,0.09578199],"study_design_scores_gemma":[0.000004859871,0.0001404649,0.9702158,0.0001637957,0.0006136731,0.0002131142,0.000811417,0.000472639,0.0004188005,0.002921792,0.02399013,0.0000333897],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.7559286,0.2088227,0.003379593,0.004579469,0.0008923929,0.00004142865,0.004361007,0.0001187237,0.02187596],"genre_scores_gemma":[0.9099556,0.08356562,0.001218542,0.0007733027,0.000345937,0.00002634099,0.001296047,0.00002660428,0.002792192],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.0225179,"threshold_uncertainty_score":0.04477364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1007985885453709,"score_gpt":0.2815390782546695,"score_spread":0.1807404897092986,"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."}}