Aquatic tail size carries over to the terrestrial phase without impairing locomotion in adult Eastern Red-spotted Newts (<i>Notophthalmus viridescens viridescens</i>)
Bibliographic record
Abstract
Many species have evolved phenotypic flexibility to adjust to seasonal changes in their environment, including seasonal breeding phenotypes that increase reproductive success. If there are limits to this flexibility, such that traits carry over across seasons, there may be costs incurred as a result of trade-offs in optimal performance. Male and female Eastern Red-spotted Newts (Notophthalmus viridescens viridescens (Rafinesque, 1820)) increase tail size for the aquatic breeding season, and reduce their tail size as they return to the terrestrial environment after reproducing. We tested whether large aquatic tails (which should increase swim performance) carry over to become larger tails in the terrestrial phase (relative to body size), and whether this incurs a cost of decreased walking speed on land. We found a strong correlation between tail size in both phases, suggesting that this trait does carry-over between seasons and environments. Tail size was positively related to locomotor speed in the aquatic phase, but we found no evidence of a locomotor trade-off associated with tail size in the terrestrial phase. Further research that tests for alternative costs of developing large aquatic tails that are then carried over to the terrestrial environment would help to clarify the evolution of this life-cycle staging trait.
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 | 0.000 |
| 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".