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Record W2547660154 · doi:10.1098/rspb.2016.1966

Chemical composition of preen wax reflects major histocompatibility complex similarity in songbirds

2016· article· en· W2547660154 on OpenAlexafffund
Joel W. G. Slade, Matthew J. Watson, T. R. KELLY, Gregory B. Gloor, Mark A. Bernards, Elizabeth A. MacDougall‐Shackleton

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMajor histocompatibility complexBiologyGeneticsMHC class IEvolutionary biologyGene

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.267
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations59
Published2016
Admission routes2
Has abstractyes

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