Factors influencing coastal cutthroat trout (Oncorhynchus clarkii clarkii) seasonal survival rates: a spatially continuous approach within stream networks
Bibliographic record
Abstract
Mark–recapture methods were used to examine watershed-scale survival of coastal cutthroat trout ( Oncorhynchus clarkii clarkii ) from two headwater stream networks. A total of 1725 individuals (≥100 mm, fork length) were individually marked and monitored seasonally over a 3-year period. Differences in survival were compared among spatial (stream segment, subwatershed, and watershed) and temporal (season and year) analytical scales, and the effects of abiotic (discharge, temperature, and cover) and biotic (length, growth, condition, density, movement, and relative fish abundance) factors were evaluated. Seasonal survival was consistently lowest and least variable (years combined) during autumn (16 September – 15 December), and evidence suggested that survival was negatively associated with periods of low stream discharge. In addition, relatively low (–) and high (+) water temperatures, fish length (–), and boulder cover (+) were weakly associated with survival. Seasonal abiotic conditions affected the adult cutthroat trout population in these watersheds, and low-discharge periods (e.g., autumn) were annual survival bottlenecks. Results emphasize the importance of watershed-scale processes to the understanding of population-level survival.
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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 | 0.000 | 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) | 0.000 | 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".