Evidence for bottom–up trophic effects on return rates to a second spawning for Atlantic salmon (Salmo salar) from the Miramichi River, Canada
Bibliographic record
Abstract
Abstract Chaput, G., and Benoît, H. P. 2012. Evidence for bottom–up trophic effects on return rates to a second spawning for Atlantic salmon (Salmo salar) from the Miramichi River, Canada. – ICES Journal of Marine Science, 69: 1656–1667. Increased return rates of consecutive repeat-spawning Atlantic salmon (Salmo salar) have been noted in the Miramichi River during the past two decades, and the short period for their reconditioning at sea suggests that they occupy the southern Gulf of St Lawrence ecosystem. A 40-year time-series of observations was used to examine linkages between return rates to a second spawning for Atlantic salmon in the Miramichi River and changes in the small fish community of the southern Gulf of St Lawrence that is potential prey for adult salmon. The positive association between the variations in the return rates of repeat spawners and the variations in the small fish biomass index early in the reconditioning year at sea provides evidence that abundant food supplies after return to sea following first spawning may be beneficial for the survival of Atlantic salmon to a second consecutive spawning. In contrast, no association was found between prey availability and return rates of alternate repeat spawners that presumably recondition outside the Gulf of St Lawrence.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".