Chemical composition of preen wax reflects major histocompatibility complex similarity in songbirds
Bibliographic record
Abstract
In jawed vertebrates, genes of the major histocompatibility complex (MHC) play a key role in immunity by encoding cell-surface proteins that recognize and bind non-self antigens. High variability at MHC suggests that these loci may also function in social signalling such as mate choice and kin recognition. This requires that MHC genotype covaries with some perceptible phenotypic trait. In mammals and fish, MHC is signalled chemically through volatile and non-volatile peptide odour cues, facilitating MHC-dependent mate choice and other behaviours. In birds, despite evidence for MHC-dependent mating, candidate mechanisms for MHC signalling remain largely unexplored. However, feather preen wax has recently been implicated as a potential source of odour cues. We examined whether the chemical composition of preen wax correlates with MHC class IIβ genotypes of wild song sparrows (Melospiza melodia). Pairwise chemical distance reflected amino acid distance at MHC for male-female dyads, although not for same-sex dyads. Chemical diversity did not reflect MHC diversity. We used gas chromatography-mass spectrometry (GC-MS) to characterize preen wax compounds, and identified four wax esters that best reflect MHC similarity. Provided songbirds can detect variation in preen wax composition, this cue may allow individuals to assess MHC compatibility of potential mates.
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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".