Data from: Paternity analysis of wood turtles (Glyptemys insculpta) reveals complex mating patterns
Bibliographic record
Abstract
Mating system characteristics are of great importance as they may influence male and female reproductive success and reproductive isolation. The wood turtle (Glyptemys insculpta) is a terrestrial freshwater species listed as endangered by the International Union for Conservation of Nature. Considering its conservation status and the paucity of information currently available on parentage relationship for the species, we performed a microsatellite analysis to study the mating system of wood turtles in the Shawinigan River (Québec). We sampled 38 clutches over two years (14 in 2006 and 24 in 2007), for a total of 248 offspring genotyped with seven microsatellite loci. The reconstructed genotypes of the fathers revealed that reproductive success in the sampled clutches varied greatly between males and are positively correlated with the number of mates and clutches sired. Frequency of multiple paternity was estimated at 37% through a consensus of three different estimation methods. Positive correlation was observed between the genetic diversity of clutches and the number of fathers. Repeat paternity, however, was observed in 88% of the clutches by the same female in successive years, which suggests either a frequent use of sperm storage, or re-mating with the same partner in successive years.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.022 |
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".