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 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) | 0.001 | 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".