The effect of low level forest harvesting on the water chemistry of boreal lakes in northeastern Ontario
Bibliographic record
Abstract
Water chemistry was monitored in twenty-one headwater lakes located in Northeastern Ontario (49°38'N, 81°00'W) for three years prior to and three years after clearcut logging in 2005. Twelve of the twenty one lakes were left undisturbed to serve as a reference condition. The percentage of the catchments harvested ranged from 5 to 42%. Principal Component Analysis and Discriminant Function Analysis revealed that the lakes were grouped in a humic-intermediate-clear gradient. Two-way Analysis of Variance within these group designations revealed few significant (p<0.05) seasonal and annual differences in water chemistry that could be attributed to forest harvesting or any relationships between the percentage of a catchment harvested and the chemical response of lakes. The results of this study are consistent with other studies across the Boreal Shield and Boreal Plain that indicate that small watersheds within the boreal forest can withstand low level harvesting pressures with minimal impacts on water chemistry.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".