Variation in the age of first reproduction: different strategies or individual quality?
Bibliographic record
Abstract
Although age at first reproduction is a key demographic parameter that is probably under high selective pressure, it is highly variable and the cause of this variability is not well understood. Two non-exclusive hypotheses may explain such variability. It could be the expression of different individual strategies, i.e., different allocation strategies in fitness components, or the consequences of individual difference in intrinsic quality, i.e., some individuals always doing better than others in all fitness components. We tested these hypotheses in the Wandering Albatross investigating relationships between the age at first reproduction and subsequent adult demographic traits. Using finite mixture capture recapture modeling, we demonstrate that the age at first reproduction is negatively related to both reproductive performances and adult survival, suggesting that individual quality was an important factor explaining variation in the age at first reproduction. Our results suggest that age at first breeding is a good predictor of quality in this long-lived seabird species.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".