Under-ice limnology of coastal valley lakes at the edge of the Arctic Ocean
Bibliographic record
Abstract
The northern coast of Ellesmere Island in the Canadian High Arctic is undergoing amplified warming that parallels the rapid decline in Arctic Ocean sea ice extent, and many lakes in this region have already shown changes in response to warming. However, biogeochemical data from High Arctic freshwaters are limited, and mostly restricted to the short, ice-free period. We sampled four coastal lakes in Stuckberry Valley (82°54′N, 66°56′W) before the onset of spring melting in 2017, 2018 and 2019, to assess biogeochemical gradients in their water columns and characteristics of their surface sediments. Despite their proximity, there were large differences in limnological properties. The two shallower lakes closer to the ocean were oxygen deficient, whereas the two deeper, more distant lakes were more oxygenated. There were pronounced vertical gradients in major ions, metals, and nutrients that suggested large differences in the extent of anaerobic microbial processes among the lakes. Morphometry and dissolved oxygen were the overriding determinants of biogeochemical differences rather than position along this short ocean–inland gradient. The diversity of limnological conditions, and the sensitivity of these characteristics to changes in ice cover, underlines the need for further study of under-ice processes in extreme northern lakes.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".