Leaf litter of invasive Chinese tallow (<i>Triadica sebifera</i>) negatively affects hatching success of an aquatic breeding anuran, the Southern Leopard Frog (<i>Lithobates sphenocephalus</i>)
Bibliographic record
Abstract
Chinese tallow (Triadica sebifera (L.) Small) is an aggressive invasive tree species that can be abundant in parts of its non-native range. This tree species has the capability of producing monocultures, by outcompeting native trees, which can be in or near wetlands that are utilized by breeding amphibians. Existing research suggests that leaf litter from invasive Chinese tallow reduces survival in larval anurans. The purpose of this study was to determine the effects of Chinese tallow leaf litter on anuran eggs. We exposed eggs of the Southern Leopard Frog ( Lithobates sphenocephalus (Cope, 1886)) at various stages of development to different concentrations of Chinese tallow leaf litter to determine survival. Eggs in the earliest stages of development that we exposed to tallow leaf litter died, regardless of concentration; however, some more-developed eggs exposed to tallow leaf litter did hatch. We determined that the greater the concentration of tallow leaf litter, the lower the dissolved oxygen and pH levels we observed. We suggest that changes in these water-quality parameters are the cause of the observed mortality of anuran eggs in our experiments. Eggs exposed to water containing tallow leaf litter with dissolved oxygen <1.59 mg/L and a pH <5.29 did not survive to hatching.
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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".