Genetic variation and phenotypic plasticity: Causes of morphological and dietary variation in Eurasian perch
Bibliographic record
Abstract
Question: What is the importance of genetic variation and phenotypic plasticity in forming the morphological difference between littoral and pelagic perch? Organism: Juveniles of Eurasian perch (Perca fluviatilis L.). Site: Enclosures (2 × 2 m) in a pond, Robacksdalen, Umea, Sweden. Methods: Adults from the littoral and pelagic habitats were bred separately and their offspring were raised in enclosures with either open water or vegetation in an artificial pond. Results: Offspring from littoral parents had a higher proportion of littoral prey types in their diet than pelagic offspring even though there were no differences in prey community between treatments. Littoral offspring had a deeper body than pelagic offspring raised in the same environment. However, most of the phenotypic variation in this experiment was explained by phenotypic plasticity: offspring from both parental types raised in open water displayed pelagic-type characteristics, whereas offspring raised in vegetation displayed littoral-type characteristics. Conclusion: Previous long-term studies on perch show that they experience a fluctuating environment due to population dynamics. The plasticity in perch could therefore be important as fluctuating environments favour plasticity.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".