Coupled landscape-lake evolution in High Arctic Canada
Bibliographic record
Abstract
We profiled five ice-covered lakes and two ice-covered fiords of Ellesmere Island at the northern limit of High Arctic Canada to examine their environmental characteristics, and to evaluate the long-term limnological consequences of changes in their surrounding landscape through time (landscape evolution). All of the ecosystems showed strong patterns of thermal, chemical, and biological stratification with subsurface temperature maxima from 0.75 to 12.15 °C; conductivities up to 98.1 mS cm1 (twice that of seawater) in some bottom waters; pronounced gradients in nitrogen, phosphorus, pH, dissolved inorganic and organic carbon, manganese, iron, and oxygen; and stratified photo synthetic communities. These ecosystems form an inferred chronosequence that reflects different steps of landscape evolution including marine embayments open to the sea, inlets blocked by thick sea ice (Disraeli Fiord, Taconite Inlet), perennially ice-capped, saline lakes isolated from the sea by isostatic uplift (Lakes A, C1, C2), and isolated lakes that lose their ice cover in summer. The latter are subject to entrainment of saline water into their upper water column by wind-induced mixing (Lake Romulus; Lake A in 2000), or complete flushing of their basins by dilute snowmelt (Lake C3 and Char Lake, which lies 650 km to the south of the Ellesmere lakes region). This chronosequence illustrates how changes in geomorphology and other landscape properties may influence the limnology of coastal, high-latitude lakes, and it provides a framework to explore the potential impacts of climate change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".