{"id":"W7132965499","doi":"","title":"Mercury Methylation and Methylmercury Demethylation in Boreal Soils and Sediment – Anthropogenic Impacts","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Methylmercury; Wetland; Sediment; Mercury (programming language); Soil water; Taiga; Organic matter; Ecosystem","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.000248916,0.0003152376,0.000190322,0.0007196266,0.0004030789,0.0007124623,0.0002080467,0.0002213602,0.0005071976],"category_scores_gemma":[0.0001854412,0.0001491146,0.0003497396,0.001150503,0.0002572881,0.0003480074,0.000272125,0.0001862856,0.00009666868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007051146,"about_ca_system_score_gemma":0.000495519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03338057,"about_ca_topic_score_gemma":0.05408651,"domain_scores_codex":[0.9998146,0.00001691821,0.00001531137,0.00006045737,0.00006133324,0.00003146271],"domain_scores_gemma":[0.9998474,0.00001292021,0.00007007725,0.000006784587,0.00004557553,0.00001721078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003374284,0.0001030692,0.8444243,0.0002195366,0.0002438917,0.0003763311,0.0004629369,0.0009295166,0.1226889,0.0002286508,0.0002546912,0.0297307],"study_design_scores_gemma":[0.000001437126,0.00005776478,0.9966337,0.000004482599,0.00001851628,0.00005726673,0.0001276531,0.0001592261,0.002373211,0.00003456359,0.0005284884,0.000003827222],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972595,0.0009938736,0.0001519934,0.00002941563,0.000008900325,0.000005390922,0.0003448218,0.000009752728,0.001196314],"genre_scores_gemma":[0.9978859,0.0007126931,0.0003337741,0.00002669267,0.00001192407,0.000004993212,0.0004836185,0.000003855469,0.0005366751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03338057,"threshold_uncertainty_score":0.06637251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02188870189068037,"score_gpt":0.3468060005052748,"score_spread":0.3249172986145945,"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."}}