More sires may enhance offspring fitness in Northern Map Turtles (<i>Graptemys</i><i>geographica</i>)
Bibliographic record
Abstract
Sexual selection theory predicts that males should be promiscuous to maximize their reproductive success, while females should be choosy. Yet females of many taxa often produce progeny sired by multiple males, indicating that promiscuity can be important for the reproductive success of females. Promiscuity may enhance the fitness of females if it increases the genetic quality, or the genetic variety, and thus the viability of their offspring. We quantified the number of sires per clutch in a population of Northern Map Turtles (Graptemys geographica (LeSueur, 1817)) in Lake Opinicon, Ontario, Canada, and tested whether the number of sires affects several metrics of viability in hatchlings. Based on the most conservative estimate, at least 71% of clutches in this population are sired by multiple males, but there was no evidence that larger clutches are sired by more males. Clutches sired by more males had higher hatching success and survival, but the differences were not statistically significant. We did not find any effect of the number of sires on hatchling morphology or locomotor performance. Collectively, our results partially support the hypothesis that promiscuity can increase the reproductive success of female Northern Map Turtles.
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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 | 0.000 | 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) | 0.002 | 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".