Birdsong signals individual diversity at the major histocompatibility complex
Bibliographic record
Abstract
The major histocompatibility complex (MHC) plays a key role in vertebrate immunity, and pathogen-mediated selection often favours certain allelic combinations. Assessing potential mates' MHC profiles may provide receivers with genetic benefits (identifying MHC-compatible mates and producing optimally diverse offspring) and/or material benefits (identifying optimally diverse mates capable of high parental investment). Oscine songbirds learn songs during early life, such that song repertoire content can reflect population of origin while song complexity can reflect early life condition. Thus birdsong may advertise the singer's genetic dissimilarity to others in the population (and, presumably, compatibility with potential mates), or individual genetic diversity (and thus condition-dependent material benefits). We tested whether song repertoire content and/or complexity signal MHC class IIβ dissimilarity and/or diversity in male song sparrows ( Melospiza melodia ). Pairwise dissimilarity in repertoire content did not predict MHC dissimilarity between males, suggesting that locally rare songs do not signal rare MHC profiles. Thus, geographical variation in song may not facilitate MHC-mediated inbreeding or outbreeding. Larger repertoires were associated with intermediate MHC diversity, suggesting intermediate rather than maximal MHC diversity is optimal. This could reflect trade-offs between resisting infection and autoimmune disorders. Song complexity may advertise optimal MHC diversity, a trait affecting disease resistance and capacity for parental care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".