Responses of Eastern Red-backed Salamander (<i>Plethodon cinereus</i>) abundance 1 year after application of wood ash in a northern hardwood forest
Bibliographic record
Abstract
Wood ash may be an effective soil amendment in North America to restore acidified and low-nutrient forest soils, but little research exists beyond its effects on soil and plants. Eastern Red-backed Salamander (Plethodon cinereus (Green, 1818)) abundance was assessed in a northern hardwood forest 1 year following an ash-addition field trial. Plots were established with fly ash and bottom ash treatments of 0, 1, 4, and 8 Mg·ha−1 (n = 4), and cover boards were positioned both with and without ash beneath. One year following ash additions, salamander abundance had increased under boards with fly ash beneath, and bottom ash had no effect. Soil pH and electrical conductivity increased under cover boards with ash beneath them and for uncovered soil, and the effects were strongest under cover boards with ash beneath. The effects of ash were generally stronger at higher dosages, and fly ash was stronger than bottom ash. The moisture holding capacity of fly ash was 60% higher than the soil and was 63% lower than the soil for bottom ash, but they had little effect on moisture of the forest floor. These results suggest that ash altered salamander abundance via soil pH and moisture and would not inhibit salamander movement over the forest floor.
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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".