Evaluating body condition in small mammals
Bibliographic record
Abstract
Body condition (energy reserves) can have important fitness consequences. Measuring condition of live animals is typically done by regressing body mass on measures of body size and using the residuals as an index of condition. The validity of this condition index was evaluated by determining whether it reflected measured fat content of five species of small mammals (yellow-pine chipmunks (Tamias amoenus Allen), bushy-tailed wood rats (Neotoma cinerea Ord), deer mice (Peromyscus maniculatus Ord), red-backed voles (Clethrionomys gapperi Vigors), and meadow voles (Microtus pennsylvanicus Ord)). We also determined whether body water could predict fat content, enabling the use of hydrogen-isotope dilution for estimating condition. For all five species, condition estimates weakly predicted fat content and more accurately predicted variation in lean dry mass and water content. The relationship between body water and fat content was inconsistent among the five species, discouraging against the general use of isotope dilution in these animals. Although ecologically important, these indices are best interpreted as explaining variation in all constituents of body composition.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".