An ontogenetic perspective on the relationship between age and size at maturity
Bibliographic record
Abstract
Summary Understanding the relationship between age and size at maturity is essential because these traits are pivotal determinants of an organism's fitness. The relationship between age and size is commonly addressed using optimization and quantitative genetic approaches. Here we argue that the value of such studies is often limited by an insufficient consideration of organismal ontogeny. On the basis of a simple conceptual framework of hierarchical resource allocation, we identify key aspects of ontogeny that prove critical to a fuller understanding of the relationship between age and size, and which, to date, have been insufficiently explored. In particular, these include intrinsic variation in growth rate within and among populations, and the physiological nature of the maturation process that co‐ordinates growth and reproductive function in an organism. We also provide some guidance to the empirical investigation of these aspects, anticipating that a wider theoretical, but especially empirical appreciation of ontogenetic detail will greatly increase the explanatory and predictive power of life‐history studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".