DIFFERENTIAL TAIL AUTOTOMY BETWEEN TWO GENETIC CLADES OF A WOODLAND SALAMANDER, PLETHODON CINEREUS
Bibliographic record
Abstract
Following the retreat of glaciers in North America, a wide diversity of organisms rapidly migrated into previously uninhabited regions, including animals with limited dispersal abilities such as amphibians. I wanted to better understand the strategies that salamanders use to aid in their dispersal abilities and to understand if patterns of post-glacial range expansion affect phenotypic traits such as anti-predator strategies. In this study, I used existing phylogeographic evidence of clade membership as a framework to examine whether red-backed salamanders (Plethodon cinereus) differed in tail autotomy behavior at the range edge versus the range core, and across the geographic range of two clades; one of limited range (the Ohio Clade) and one that has dispersed north along the Atlantic coast into Canada, westward, and south into Michigan and Indiana (the Northern Clade). I hypothesized that salamanders belonging to the Northern Clade and salamanders belonging to range-edge groups would exhibit high tail autotomy frequencies and a greater degree of antipredator postautotomy characteristics. I conducted lab experiments and used museum specimens to examine tail autotomy frequencies and other tail autotomy characteristics, including latency to autotomize under predation pressure, duration of tail movement following autotomy, postautotomy tail movement undulations, and tail regrowth. In my lab experiments, I found significantly higher tail autotomy frequencies within range-core populations and significantly greater postautotomy tail movement duration in my sampled populations from the Northern Clade. Further, I found significantly greater frequencies of autotomy in the Northern Clade in my museum specimen analysis. Therefore, I conclude that Plethodon cinereus exhibits geographic variation in tail autotomy frequencies, although the observed patterns of tail autotomy in this study did not align with my initial hypotheses and instead appear to be influenced by several other unidentified variables.
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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 | 0.001 |
| 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".