Amphibian distribution and habitat quality in the boreal forests of northwestern Ontario
Bibliographic record
Abstract
Decisions about habitat conservation are often based on estimates of population size, and therefore rely on the assumption that population abundance reflects habitat quality and better fitness. However, some species can be as, or more, abundant in low-quality than high-quality habitats, where resource availability and fitness are low. Decisions based solely on abundance therefore run the risk of reducing the availability of good-quality habitats because of the assumption that habitats with low abundance are expendable. To test whether amphibian abundance is positively correlated with fitness in the boreal forests of northwestern Ontario, I compared the abundance and body condition of amphibians in logged and unlogged mixed and conifer forest. Body condition and abundance of adult American toads can be used as an index of habitat quality. Alternatively, wood frogs and juvenile American toads may be subject to interference, competitive differences or perceptual constraints, and the use of their abundance as an index of habitat quality is ill-advised without further work on resource selection, population recruitment and intraspecific interactions in the boreal forest.
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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 | 0.000 |
| 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 | 0.000 | 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".