Assortative pairing by telomere length in King Penguins (<i>Aptenodytes patagonicus</i>) and relationships with breeding success
Bibliographic record
Abstract
Telomeres are noncoding genetic repeats protecting the ends of linear chromosomes. Long telomeres are often associated with high individual survival, and interindividual variation in telomere length has recently been proposed as a proxy for individual quality. Therefore, one might expect individuals of either sex with long telomeres to be of higher intrinsic quality and to be preferred in the context of mate choice. Thus, in sexually monomorphic species where individuals discriminate mates on the basis of signals of intrinsic quality, mate choice should lead to assortative pairing by telomere length, and it should be associated with breeding performance. We tested these two predictions in the King Penguin (Aptenodytes patagonicus J.F. Miller, 1778), a sexually monomorphic seabird. Over 3 years of study and 73 penguin pairs under contrasting environmental conditions, we found strong assortative pairing by telomere length. Interestingly, only female telomere length was positively associated to chick survival up to fledging, and this relationship was only apparent when foraging conditions at sea were average. The positive link between telomere length and breeding success confirmed that telomere length is somehow related to individual biological state at a given time. The proximate mechanisms by which birds assess individual state related to telomere length remain to be discovered.
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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 | 0.001 |
| 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".