Measuring sexual size dimorphism in the yellow-pine chipmunk (<i>Tamias amoenus</i>)
Bibliographic record
Abstract
Body size was examined in the yellow-pine chipmunk (Tamias amoenus), which is reported to have female-biased sexual size dimorphism. Our objective was to determine if yellow-pine chipmunks from the Kananaskis Valley were dimorphic. Three methods were used. We compared body mass, 5 univariate components of body size, and multivariate centroids between males and females, and quantified measurement error. Females were significantly heavier (10-20%) and had a longer body (4%) and a longer (0.9%) and wider (2.2%) skull than male chipmunks, as well as being larger in overall size of skeletal tissue (structural body size). Multivariate methods such as discriminant functional analysis can robustly determine whether the sexes are significantly different in overall structural body size. However, univariate measures of body size provide an intuitively clear index of the magnitude of the difference in size of a particular character between the sexes.
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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) | 0.002 | 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".