Influences of migration phenology on survival are size-dependent in juvenile Atlantic salmon (<i>Salmo</i> <i>salar</i>)
Bibliographic record
Abstract
Long-distance migratory species can reduce mortality risks by synchronizing the migration event and create confusion by swamping predators with high densities. To reduce confusion, predators are known to primarily select aberrant prey. We hypothesized that at the start of their sea sojourn, particularly small and large Atlantic salmon (Salmo salar L., 1758) would spread the risk by also migrating at other times of the year. Based on data from the Norwegian river Imsa between 1976 and 2015, we found that juveniles, 14–19 cm in total length, started their sea sojourn during a short period between late April and early June. However, more than 20% of fish 13 cm or shorter migrated downstream between October and March, whereas 55% of fish 20 cm or longer migrated downstream between July and September. The regular-sized, spring-migrating juveniles had 2–3 times higher survival at sea than similar-sized conspecifics migrating to sea at other times of the year. The survival at sea for smaller juveniles was not improved by migration in spring relative to winter, and the survival of the largest juveniles was similar in spring and summer. Thus, the migration phenology appears adapted to survival in a high-risk environment by changing the timing according to their sizes.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".