Survival of Amazonian Tadpoles Under Harsh Water-Limiting Conditions
Bibliographic record
Abstract
Tadpoles of some anuran species are known to survive out of water, but information is scarce or nonexistent for most species. We experimentally tested the survival ability of Amazonian tadpoles of six species out of water in conditions that simulated pond drying. Specifically, we tested the hypothesis that tadpoles typical of habitats subject to fast drying would have higher capacity to survive without free water. We found higher survival rates for some species that usually occur in temporary ponds and the lowest one for a species from perennial ponds. However, we also found species from temporary ponds and streams with intermediate tolerance to desiccation. Tadpole survival differed among species and increased in function of body mass but was not related to the probability of each species being subject to periods without water in their habitats. Therefore, we reject the hypothesis that tadpole survival in the absence of water is a simple function of the probability of ponds drying.
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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 | 0.000 | 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".