Cutaneous tactile sensitivity before and after tail loss and regeneration in the leopard gecko (<i>Eublepharis macularius</i>)
Bibliographic record
Abstract
ABSTRACT Amongst tetrapods, mechanoreceptors on the feet establish a sense of body placement and help to facilitate posture and biomechanics. Mechanoreceptors are necessary for stabilizing the body while navigating through changing terrains or responding to a sudden change in body mass and orientation. Lizards such as the leopard gecko (Eublepharis macularius) employ autotomy – a voluntary detachment of a portion of the tail – to escape predation. Tail autotomy represents a natural form of significant (and localized) mass loss. Semmes–Weinstein monofilaments were used to investigate the effect of tail autotomy (and subsequent tail regeneration) on tactile sensitivity of each appendage of the leopard gecko. Prior to autotomy, we identified site-specific differences in tactile sensitivity across the ventral surfaces of the hindlimbs, forelimbs and tail. Repeated monofilament testing of both control (tail-intact) and tail-loss geckos had a significant sensitization effect (i.e. decrease in tactile threshold, maintained over time) in all regions of interest except the palmar surfaces of the forelimbs in post-autotomy geckos, compared with baseline testing. Although the regenerated tail is not an exact replica of the original, tactile sensitivity is shown to be effectively restored at this site. Re-establishment of tactile sensitivity on the ventral surface of the regenerate tail points towards a (continued) role in predator detection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".