Interactive effects of life history and season on size‐dependent growth in juvenile <scp>A</scp>tlantic salmon
Bibliographic record
Abstract
Abstract Size‐dependent growth (SDG) is an important process in structuring populations as well as determining life history outcomes. Despite its importance, there have been few investigations from observational studies focusing on the interaction between life history decisions and SDG. In this study, we used data on individually tagged Atlantic salmon from both the laboratory and the field to investigate differences in SDG among two life history groups, parr and smolts. In the laboratory, we found little evidence of SDG in parr but seasonally dependent SDG in the smolt group. Smolts showed at strong compensatory response over the winter months just prior to the smolt transformation window. In the field, we found little evidence of SDG early in ontogeny (i.e., age 0+ fall and winter). There was some evidence of depensatory growth (positive SDG) during the age 1+ spring among both life history groups that may reflect random habitat variation or the monopolisation of resources. After the age 1+ spring, we found that smolts were more likely to show a compensatory effect (negative SDG) than parr. This effect was strongest, as they approached the smolt window in the spring of their age 2+ year. These results suggest (i) SDG is common in Atlantic salmon; however, the form and extent of life history depends on (ii) season and (iii) life history. For individuals that adopt a smolt life history, trade‐offs between freshwater survival and sea survival may lead to a convergent growth pattern, as they approach the smolt migration window.
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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) | 0.002 | 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".