Synthesis of limnological data from lakes and ponds across Arctic and Boreal Canada
Bibliographic record
Abstract
A compilation of published and new limnological data from 1489 shallow lakes and ponds in northern Canada, sampled between 1979 and 2009, revealed significant patterns that correlated with landscape features and climate. Lakes and ponds underlain by Archean or Proterozoic bedrock had lower specific conductivity and pH. Vegetation cover had a lesser influence on these parameters. Forested landscapes tended to have higher phosphorus and nitrogen, as did younger rock types. Dissolved organic carbon was higher, but dissolved inorganic carbon was lower in forested regions. Phytoplankton biomass of the surface waters, as estimated by chlorophyll a concentrations, was positively correlated with July air temperature and nutrients, and was higher in forested relative to polar desert regions. There were no significant differences in the measured limnological variables between shallow (<2 m depth) and deep lakes (>2 m); however, all water chemistry parameters were negatively correlated with depth. Despite large variability within and among regions, spatial trends in water chemistry were associated with geology, vegetation, and climate at a continental scale.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 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".