Repeated Origin and Loss of Adhesive Toepads in Geckos
Bibliographic record
Abstract
Geckos are well known for their extraordinary clinging abilities and many species easily scale vertical or even inverted surfaces. This ability is enabled by a complex digital adhesive mechanism (adhesive toepads) that employs van der Waals based adhesion, augmented by frictional forces. Numerous morphological traits and behaviors have evolved to facilitate deployment of the adhesive mechanism, maximize adhesive force and enable release from the substrate. The complex digital morphologies that result allow geckos to interact with their environment in a novel fashion quite differently from most other lizards. Details of toepad morphology suggest multiple gains and losses of the adhesive mechanism, but lack of a comprehensive phylogeny has hindered efforts to determine how frequently adhesive toepads have been gained and lost. Here we present a multigene phylogeny of geckos, including 107 of 118 recognized genera, and determine that adhesive toepads have been gained and lost multiple times, and remarkably, with approximately equal frequency. The most likely hypothesis suggests that adhesive toepads evolved 11 times and were lost nine times. The overall external morphology of the toepad is strikingly similar in many lineages in which it is independently derived, but lineage-specific differences are evident, particularly regarding internal anatomy, with unique morphological patterns defining each independent derivation.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".