Capture-recapture data with partially known birth date in four populations of yellow-bellied toads
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
1. Patterns of actuarial senescence can be highly variable among species. Previous comparative analyses revealed that both age at the onset of senescence and rates of senescence are linked to species position along the fast-slow life-history continuum. As there are few long-term datasets of wild populations with known-age individuals, intraspecific (i.e. between-population) variation in senescence is understudied and limited to comparisons of wild and captive populations of the same species, mostly birds and mammals. 2. In this paper, we examined how population position along the fast-slow life history continuum affects intraspecific variation in senescence in an amphibian, Bombina variegata. 3. We used capture-recapture data collected in four populations with contrasting life history strategies. Senescence trajectories were analyzed using Bayesian capture-recapture models. 4. We show that in fast populations the onset of actuarial senescence was earlier and individuals aged at a faster rate than individuals in slow populations. 5. Our study provides one of the few empirical examples of among-population variation in actuarial senescence patterns in the wild and confirms that the fast-slow life history gradient is associated with both macroevolutionary and microevolutionary patterns of actuarial senescence.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it