Variation in female reproductive quality and reproductive success of male Midland Painted Turtles (<i>Chrysemys picta marginata</i>)
Bibliographic record
Abstract
Although mate number is perceived to be the primary factor affecting male reproductive success in polygynous systems, differences in female reproductive qualities may also influence variation in male reproductive success. We combined 32 years of data on variation in reproductive qualities (clutch size and clutch frequency) of female Midland Painted Turtles ( Chrysemys picta marginata Agassiz, 1857) with genetic data on patterns of repeated paternity (i.e., stored sperm use) and multiple paternity to examine the potential influence on male reproductive success. Over 24 years (1983–2006), the number of reproductive females each year averaged 84 (minimum–maximum = 62–106) and, on average, 23% (minimum–maximum = 6%–40%) produced two clutches (intraseasonally). Among females with reproductive histories spanning 5–24 years (N = 167), 26% of individuals produced only one clutch annually, whereas 74% produced two clutches within a season. Among just intraseasonally iteroparous females, second-clutch production varied from 7% to 50%. Repeated paternity was observed in 97.5% of 40 paired clutches and 44% of 9 among-year comparisons of clutches from consecutive years. The frequent use of stored sperm to fertilize sequential clutches within and potentially among years can substantially increase a male’s reproductive success, particularly if males can base mating decisions on phenotypic characteristics correlated with female quality.
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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".