Age determination in yellow-pine chipmunks (<i>Tamias amoenus</i>): a comparison of eye lens masses and bone sections
Bibliographic record
Abstract
Virtually all biological characteristics of organisms change with age, and thus, to assess the impact of these changes, accurate aging techniques are essential. However, many current methods are unable to accurately distinguish among adults of different ages. We determined the age of yellow-pine chipmunks (Tamias amoenus) from the Rocky Mountains of Alberta using eye lens masses, annuli from mandible sections, and annuli from femurs. Each of these methods was assessed against nine known-age animals and seven animals that had not been caught previously and were presumed to be juveniles. Eye lens masses could distinguish juveniles from adults but not adults of different ages. Mandibular sections were not practical in this species because of excessive tearing during sectioning. Femoral sections precisely predicted age. We found that the number of adhesion lines, minus one, accurately represented the ages of adults ranging from 1 to 5 years old. Femoral annuli have not previously been used to age mammals and our results suggest that they may be useful in aging other mammals, especially rodents.
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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 | 0.001 | 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 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".