Estimating cross-population variation in juvenile compensation in survival for bull trout (<i>Salvelinus confluentus</i>): a Bayesian hierarchical approach
Bibliographic record
Abstract
Juvenile compensation in survival, quantified as compensation ratio (CR), is critical for fish population persistence. At present, no estimate of this key parameter exists for bull trout (Salvelinus confluentus). This species has a conservation listing and is targeted by recreational angling in portions of its range. Obtaining accurate estimates of CR is crucial to aid recovery efforts and develop sustainable fisheries policies. This investigation develops a hierarchical Bayesian meta-analysis to estimate CR and explore the functional form of stock–recruitment for bull trout. Results show bull trout have high scope for density-dependent compensation evidenced by CR estimates generated herein and by previous research. This demonstrates changes in habitat quality and quantity are likely limiting recovery of many populations. However, owing to lack of data, variance is high. Limitations in available data for this analysis are due to the high cost and operational difficulty of sampling, and high uncertainty in CR estimates. This study highlights the importance of collecting additional paired stock–recruitment data to facilitate future investigations and reduce variance in CR estimates for bull trout.
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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 | 0.021 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".