Energetic state and the continuum of migratory tactics in brown trout (<i>Salmo trutta</i>)
Bibliographic record
Abstract
Alternative migratory tactics, like partial migration, are common in many taxa. The proximate and ultimate drivers underpinning these strategies are unclear, though factors like condition and energetic status have been posited as important predictors. We sampled and PIT-tagged 1882 wild brown trout (Salmo trutta) prior to the first so-called decision window and explored the links between migratory tactics (residency, autumn or spring migration) and body metrics (length and condition), lipids (triglycerides and cholesterol), and sex in 150 randomly selected individuals. We found that more females adopted the autumn and spring migration tactic than males, while more males adopted the residency tactic than females, likely reflecting sex-biased benefits in anadromy. We also found that autumn migrants were in poorer condition prior to the presumed first decision window than spring migrants and residents. Lastly, we found that both condition and cholesterol were positively correlated to the timing of migration, such that individuals in poorer condition and (or) with lower cholesterol migrated earlier. Collectively, these results suggest that energy depletion is an important factor in determining migratory strategy, including timing.
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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 | 0.000 |
| 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".