The effect of clearcut logging and forest fires on hypolimnetic oxygen depletion rates in remote Canadian Shield lakes /
Bibliographic record
Abstract
Thirty-eight oligotrophic lakes located around the Reservoir Gouin in central Quebec (48°N, 75°W) were sampled over three years to test the hypothesis that forest clearcutting and fires should be reflected in both higher nutrient export rates and ultimately in greater areal hypolimnetic oxygen deficit rates (AHOD). Significant differences in estimated total phosphorus export rates across treatments were found. However, no effect of clearcutting or forest fire on hypolimnetic oxygen consumption rates could be demonstrated as the result of a much greater and confounding variation in the effect of lake morphometry and the absence of information on the role of catchment-derived organic matter on the AHOD. Consequently, only lake morphometry (hypolimnetic volume to hypolimnetic surface area ratio) served as a predictor of the AHOD. Covariation of mean hypolimnetic water temperature with morphometric variables underlines the influence of lake morphometry on heat dynamics and hypolimnetic respiration rates in these lakes. This research made considerable use of specialized data manipulation techniques involving a relational database management system, owing to the size of the dataset used (114 lake-years of data). The specific approach used in this thesis is presented in an appendix.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".