Early experience and reproductive morph both affect brain morphology in adult male Chinook salmon (<i>Oncorhynchus tshawytscha</i>)
Bibliographic record
Abstract
It is clear that brain size and structure can be greatly influenced by the environment, and in fish, factors such as habitat complexity, rearing environment, and reproductive status have been shown to affect brain morphology and behaviour, but it is unclear how long these effects last. The objective of the current study was to investigate variability in overall brain size and particular brain regions of male Chinook salmon (Oncorhynchus tshawytscha) through the evaluation of potential driving forces — environment and reproductive morph. By comparing fish from different rearing environments and different male reproductive morphs (hooknose versus jack), the current research assessed the influence of each of these factors on overall brain size and on select brain regions. Male hooknose salmon had relatively smaller brains, once corrected for body size, than male jack salmon, suggesting possible trade-offs between somatic and brain development. Fish reared in hatchery environments but released into the wild as presmolts still had relatively larger brains than their wild counterparts, despite sharing wild habitats for over 3 years, suggesting persistent effects of hatchery rearing. Taken together, these results show that the difference in reproductive morphs can substantially impact brain morphology and that short-term environmental influences can have persistent effects throughout ontogeny.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".