Spatial variability in adult brook trout (<i>Salvelinus fontinalis</i>) survival within two intensively surveyed headwater stream networks
Bibliographic record
Abstract
Headwater stream networks are considered heterogeneous riverscapes, but it is challenging to characterize spatial variability in demographic rates. We estimated site-scale (50 m) survival of adult (>age 1+) brook trout (Salvelinus fontinalis) within two intensively surveyed headwater stream networks by applying an open-population N-mixture approach to count data collected over two consecutive summers. The estimated annual apparent survival rate was 0.37 (95% CI: 0.28–0.46) in one network and 0.31 (95% CI: 0.15–0.45) in the other network. In both networks, trout survival was higher in stream sites characterized by more abundant pool habitats. Trout survival was negatively associated with mean depth in one network and positively associated with stream gradient in the other. Stream temperature was not related to trout survival in either network, possibly because the majority of sites were thermally suitable. A similar analytical approach can be useful for inferring survival rates when count data are available over space and time but individual tagging is not feasible.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".