Age and experience affect the reproductive success of captive Loggerhead Shrike (<i>Lanius ludovicianus</i>) subspecies
Bibliographic record
Abstract
Two explanations are often used to interpret the positive relationship between reproductive success and age: (1) trade-offs between current and future breeding and (2) age-related improvements in competence. Captive populations provide a unique opportunity to test these explanations because several mechanisms that result in age-related improvements in competence are managed. We modelled the effect of age and experience on the reproductive success of captive migrant Loggerhead Shrike (Lanius ludovicianus L., 1766) subspecies (formerly Lanius ludovicianus migrans W. Palmer, 1898). Female shrikes had the highest reproductive success during mid-life and lower success at 1–2 years of age and over 10 years. Both experienced male and female shrikes had higher fledgling success than inexperienced individuals. Although captive populations breed in controlled settings with few limitations, this work suggests that both explanations (i.e., trade-offs and age-related improvements in competence) are important for understanding reproductive success. Furthermore, management of the captive shrike population can be informed by these relationships to maximize the number of young produced for release to supplement the wild population.
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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".