Estimating the transition of individuals between life stages
Bibliographic record
Abstract
Over their lifetimes, individuals of a species transition from one stage of their life cycle to the next (for example, a nonreproductive juvenile will mature to a reproductive adult). Estimating the age at which these transitions occur can be complex for a variety of reasons. A fundamental, generalizable way to assess the mean age of transition along with a standard deviation of the distribution of the transition is developed. We propose and statistically develop a method that is easy to use, requires only one data collection period, and provides reliable estimates for the mean and the standard deviation of the transition point. Our results for the case studies for one species, Carnegiea gigantea , using eight independent real‐world datasets, are robust, confirming the validity and usefulness of the proposed technique. We develop an important ecological metric that quantifies the age at which a species transitions from one stage to another in its life cycle. This is a basic ecological metric that is often assumed, but that until now has been difficult to quantify practically for many species. This metric is easy to use (we provide a spreadsheet that does all the calculations) and essential for all life scientists, regardless of species, life form, or ecosystem of study. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.001 | 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 | 0.001 |
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 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".