Minimal soil quality impact by cold season pasture management in Vermont
Bibliographic record
Abstract
Small-scale dairy farming is economically challenging; however, management intensive grazing practices have allowed many farms to become profitable. Traditional barn housing during cold seasons is a large expense and could be adapted to further economic gains. In this study, three cold season pasture management practices, such as bedded pack (BP) compost amendment, out-wintering (OW) on pasture, and stockpiling (SP) mixed grass–legume pasture forage, were evaluated for impact to soil and forage quality within pasture. Composite soil and forage samples were collected during spring and autumn 2009–2010 for soil physical, chemical, and biological analyses (nematode community structure) and forage quality. Out-wintering favored fungal decomposition (P = 0.089), and all treatments promoted soil food web structure, with a mean structure index value of 63 ± 1.71 SE. Negative impacts to soil health, including physical structure and soil chemistry, were not detected. Impacts to forage quality included decreased degradable protein under SP (P = 0.055) and decreasing relative feed value following SP and BP treatment application (P = 0.025). The small sample size (total n = 16 or eight pairs) and high variability require cautious interpretation, yet minimal negative effects of implementing BP, OW, and SP practices were detected.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".