Data from: Linking innate immunogenetic variation with phenotypic traits in a wild population of tree swallows, Tachycineta bicolor
Bibliographic record
Abstract
Unravelling the genetic basis of phenotypic variation among individuals is an important step in our understanding of evolution. Recent studies of innate immune genes, such as β -defensins, revealed that these genes had high levels of polymorphism. However, researchers have yet to quantify the effects of such variability on immune responses and fitness-related traits in wild populations. In this study, we assessed how the variability at six avian β -defensin (AvBD) genes was linked to an immune function and reproductive success in adult tree swallows (Tachycineta bicolor). We investigated the links between genetic variations using single nucleotide polymorphisms at AvBD genes, immune function as the bacterial killing ability (BKA) and fledging success. We assessed how female immunogenetics were linked to the presence of eggshell bacteria in their clutches and hatching success. We found weak associations between the presence of AvBD genes, BKA and eggshell bacteria. Our results suggested that homozygosity at some loci may be advantageous for defence against bacteria. Variability at β -defensin genes was not related to either hatching or fledging success. BKA of parents was positively linked with fledging success. More studies are needed to assess whether or not β -defensin genes are significantly affecting fitness-related traits in wild populations.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.009 |
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".