Seasonal fluctuations in the bone microstructure of <i>Sciurus vulgaris fuscoater</i> humeri: a case study using phenomics on µCT-scans
Bibliographic record
Abstract
Abstract Sciurus vulgaris Linnaeus, 1758, the red squirrel, is a small, mostly arboreally living rodent, spread across the Palearctic. It is mostly vegetarian, feeding on plants, fungi and seeds, and is less active in the winter months, but does not hibernate. In this lateral study, the humeri of the subspecies Sciurus vulgaris fuscoater , the Central European red squirrel, were analysed to uncover potential intraspecific variation between individuals found in different seasons. The µCT-scans were obtained with a resolution of 26 microns. Five bone parameters were calculated and statistically evaluated with regards to seasonal variations: total volume, bone volume, endocortical surface, cortical thickness, and average trabecular thickness. Bone volume, trabecular thickness and endocortical thickness correlate with bone size, whereas cortical thickness does not. Seasonal differences were observed between the warmer summer and autumn months versus the colder winter and spring months for all parameters. We, speculatively, relate the observed seasonal variation to nutrient intake, notably calcium. These results offer a deeper understanding of intraindividual variation in red squirrels, that may be useful in further ecological, taxonomic, and paleontological research.
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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 | 0.002 | 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".