Linking intronic polymorphism on the CHD1‐Z gene with fitness correlates in Black‐tailed Godwits <i>Limosa l. limosa</i>
Bibliographic record
Abstract
We show that variation in an intronic length polymorphism in the CHD1‐Z gene in Black‐tailed Godwits Limosa l. limosa is associated with fitness correlates. This is the second example of the CHDZ‐1 gene being correlated with fitness, a previous study having established that Moorhens Gallinula chloropus carrying the rare Z* allele have reduced survival. In Godwits, however, carriers of the Z* allele (374 bp) fared better than those with the more frequent Z allele (378 bp) with respect to body mass, plumage ornamentation, reproductive parameters and habitat quality. The Z* allele was found in 14% of 251 adult birds from nature reserves, but was absent from 33 birds breeding in intensively managed agricultural lands. Males and females with the Z* allele had less extensive breeding plumage, and females had a higher body mass, bred earlier and had larger eggs. There were no significant differences in annual survival between birds with and without the Z* allele. DNA isolated from museum skins demonstrated that this polymorphism was present at low frequency in 1929. We speculate that strong asymmetrical overdominance may explain the low frequency of the Z* allele and that genetic linkage to causal genes might be an explanation for the phenotypic correlations. Our findings suggest a degree of cryptic genetic population structuring in the Dutch Godwit population.
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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 | 0.001 | 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".