Temporal and Longitudinal Mercury Trends in Burbot (<i>Lota lota</i>) in the Russian Arctic
Bibliographic record
Abstract
Current understanding of mercury (Hg) dynamics in the Arctic is hampered by a lack of data in the Russian Arctic region, which comprises about half of the entire Arctic watershed. This study quantified temporal and longitudinal trends in total mercury (THg) concentrations in burbot ( Lota lota ) in eight rivers of the Russian Arctic between 1980 and 2001, encompassing an expanse of 118 degrees of longitude. Burbot THg concentrations declined by an average of 2.6% annually across all eight rivers during the study period, decreasing by 39% from 0.171 μg g –1 wet weight (w.w.) in 1980 to 0.104 μg g –1 w.w. in 2001. THg concentrations in burbot also declined by an average of 1.8% per 10° of longitude from west to east across the study area between 1988 and 2001. These results, in combination with those of previous studies, suggest that Hg trends in Arctic freshwater fishes before 2001 were spatially and temporally heterogeneous, as those in the North American Arctic were mostly increasing while those in the Russian Arctic were mostly decreasing. It is suggested that Hg trends in Arctic animals may be influenced by both depositional and postdepositional processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".