Effect of environmental stress on fluctuating asymmetry in certain morphological traits in Drosophila ananassae: nutrition and larval crowding
Bibliographic record
Abstract
The association of fluctuating asymmetry and phenotypic and genetic variability with environmental stress was investigated using poor nutrition and larval density as stresses on 10 recently collected isofemale lines of Drosophila ananassae Doleschall, 1858. Trait means for different morphological traits were reduced by stress, whereas phenotypic and genetic variability increased. The levels of fluctuating asymmetry and positional fluctuating asymmetry were similar in flies reared on poor and standard media. In constrast, there is a significant difference in both asymmetry measures in the flies reared at different larval densities for all traits. However, when asymmetry values across all traits were combined into a single index, composite fluctuating asymmetry, significant differences were found in males and females reared at different larval densities but not under nutritional stress. Moreover, composite fluctuating asymmetry is higher in males than in females, suggesting that males are more vulnerable to developmental stress. The results suggest that trait means are more sensitive to stress than fluctuating-symmetry measures and that the effect of stress is trait- and sex-specific. Generalizations based on the use of fluctuating asymmetry as an indicator of environmental stress in D. ananassae should therefore be used with caution.
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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) | 0.000 | 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".