The Effect of Age on Survival Is Similar in Males and Females of an Aquatic Insect Species
Bibliographic record
Abstract
Age is a critical intrinsic factor that influences the probability of survival of organisms on Earth. In many animals, the lifestyles and habitat occupancy of males and females are so different that the effect of age could be sex-dependent. To reveal such patterns in wild animal populations, we here use a natural population of the Mediterranean demoiselle Calopteryx haemorrhoidalis Vander Linden (Calopterygidae: Zygoptera) in Northeast Algeria to analyze the influence of age and sex on survival probability using daily capture–mark–recapture. We used stepwise model selection on Cormack–Jolly–Seber models that explain recapture and survival probability, including age and sex as covariates. We marked a total of 214 adults throughout the study period (41 days). The sex ratio did not deviate from unity. Recapture probability depended on sex and time, with a slightly higher recapture probability in males (0.30 [95% CI: 0.27–0.35]) than females (0.26 [0.22–0.30]). The survival probability was slightly higher in females (0.89 [0.86–0.91]) than males (0.86 [0.82–0.88]). The best model for the survival probability included an additive effect of sex and age, indicating that the survival probability of both sexes declined with age. Interestingly, the lifespan of some individuals reached 119–130 days, which is surprisingly long compared to other temperate damselflies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".