Fine spatial scale phenotypic divergence in wood frogs (Lithobates sylvaticus)
Bibliographic record
Abstract
I studied local divergence in growth, a trait previously shown to be both phenotypically plastic and heritable, among wood frog (Lithobates sylvaticus (LeConte, 1825)) tadpoles inhabiting four ponds within a continuous woodland. Mark–recapture results revealed very low levels of migration among ponds as close as 35 m and no more than 185 m apart. Common garden experiments conducted at two temperatures revealed consistent year-to-year patterns of phenotypic divergence in tadpole growth performance among the four pond populations. The divergence in growth performance was conserved when controlling for parental effects via half-sibling experiments. Results of cross-transplant experiments suggest that the divergence in tadpole growth reflected either genetic drift or adaptation to local pond conditions. Taken together, the results suggest that divergence in growth performance among the tadpoles from the four ponds is the result of selection or genetic drift reinforced by low levels of gene flow among pond populations.
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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 | 0.001 |
| 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".