A simple, low‐cost method to age mammals? An alternative to cementum annuli analysis
Bibliographic record
Abstract
Abstract One of the most common and ubiquitous methods to age mammals is by counting the cementum annuli in molars, premolars, incisors, or canines. Despite the ubiquity and perceived simplicity of the method, cementum annuli analysis can be time‐consuming, expensive, inaccurate, and imprecise, and require specialized equipment. Using beavers ( Castor canadensis ) as a test species, we developed a straightforward method to age mammals that requires little specialized equipment. The method consists of: (1) digitizing longitudinally sectioned teeth and measuring the proportion of tooth surface area comprised of cementum (“proportion cementum”), (2) evaluating the relationship between proportion cementum and specimen age (determined from either known‐age samples or cementum annuli analysis), and (3) using the modeled relationship to estimate the age of other individuals based solely on proportion cementum. The relationship between proportion cementum and age was strongly correlated ( R 2 = .97–.98 depending on observer), similar between observers, and similar between known‐age specimens and those aged via cementum annuli analysis. Using this proportion cementum method, two independent observers accurately predicted the age of 80%–84% of specimens within 0.5 year and 96%–98% within 1 year. We suggest this aging method will likely work with most mammal species given the relatively consistent deposition of cementum throughout mammals' lives and has promise to be a simple and quick alternative to cementum annuli analysis regardless of whether one develops proportion cementum models using known‐age specimens or those aged via alternative methods.
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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 | 0.001 |
| 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) | 0.001 | 0.002 |
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".