Seasonal variation in body mass and locomotor kinetics of the fat‐tailed dwarf lemur (<i>Cheirogaleus medius</i>)
Bibliographic record
Abstract
The fat-tailed dwarf lemur (Cheirogaleus medius) is unusual among primates in storing large amounts of fat subcutaneously prior to hibernating during the winter months. In doing so, it increases its body mass by more than 50%, with a substantial weight gain in the tail. This seasonal increase in mass provides a unique natural experiment to examine how changes in body mass affect substrate reaction forces during locomotion. As body mass increases, it is expected that the limbs of the fat-tailed dwarf lemur will be subjected to greater peak vertical substrate reaction forces during quadrupedal walking. However, whether or not these peak substrate reaction forces will increase proportionally across forelimbs and hindlimbs as body mass increases is unknown. Substrate reaction forces were collected on four adult C. medius walking quadrupedally on a 28-mm pole attached to a force platform. Peak vertical substrate reaction forces (Vpk) (N) were analyzed and compared for a cross-sectional sample of different body masses (180-300 g). Forelimb and hindlimb Vpk were positively correlated with body mass, with hindlimb Vpk always higher than forelimb Vpk. However, the rate at which Vpk increased relative to body mass was higher for the hindlimb than the forelimb. This disproportion in weight distribution between the forelimbs and hindlimbs as body mass increases appears to be linked to the accumulation of fat in the tail. It is likely that storing fat in the tail region may shift the center of mass more caudally, from a more cranial position when the tail is thinner. Such a caudal shift of the center of mass-either morphological or dynamic-is believed to have played an important role in the functional differentiation of the limbs and the evolution of locomotor modes of several tetrapod groups, including dinosaurs and primates.
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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 | 0.000 |
| 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) | 0.001 | 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".