Bone labeling experiments and intraskeletal growth patterns in captive leopard geckos (<i>Eublepharis macularius</i>)
Bibliographic record
Abstract
An understanding of the dynamics of bone growth is key to interpreting life-history parameters of vertebrates. In this study, we used fluorochrome labels in captive leopard geckos (Eublepharis macularius) to track bone growth and intraskeletal variability from embryonic to adult growth stages. Thirteen individuals were administered fluorochromes from pre-hatching to 4 years of age. The left tibia, fibula, femur, humerus, radius, and ulna were examined histologically and compared for differences in the number of labels within and between individuals at each sampled growth stage, and the amount of bone growth between labels was calculated. Results suggest that limb elements had differing growth rates; the fibula grew the fastest per day on average and the femur grew the slowest per day on average. All labels administered in ovo were still present in all limb elements in adults except for the tibia, suggesting growth marks are not lost in most elements and accurate calculations of growth rates could be performed in individuals up to 3 years old. All ex ovo labels were accounted for; however, when two fluorochromes were administered 3 weeks apart, the labels could not be differentiated from each other due to the new bone not being deposited at a quantifiable level. Overall, the tibia in leopard geckos is the least reliable limb bone to use for skeletochronology and the humerus, radius, and fibula preserve the longest growth record. This research highlights that, as in other extinct and extant animals, patterns of bone growth are not consistent across reptiles. This study adds to the growing body of knowledge on growth variability in reptiles.
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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 | 0.001 | 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".