Assessing the impacts of stream habitat and land use variables on population and community structure of salmonids of Prince Edward Island
Bibliographic record
Abstract
To determine the impact of land use practices and run-off events on salmonid communities, I examined salmonid populations (Atlantic salmon, Salmo salar, brook trout, Salvelinus fontinalis, and rainbow trout, Oncorhynchus mykiss) at twenty-seven sites on nine rivers located across Prince Edward Island throughout the summers of 2001 and 2002. Multiple regression models were developed using various stream and watershed characteristics to predict biotic variables (density, percent habitat saturation, and condition factors) and stable isotope values. Five rivers were sampled in 2002 to use in a cross-validation study to test the models. Six models were developed (brook trout density, variability in total density, total percent habitat saturation, variability in total percent habitat saturation, 1 + brook trout condition factor, and δ15N values). Although all models explained a significant proportion of the variability in the nine original rivers (r2 values ranging from 0.374 to 0.985), only that describing δ 15N values proved valid when tested in the cross-validation study.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".