Permeable Synthetic Covers for Controlling Emissions from Liquid Dairy Manure
Bibliographic record
Abstract
Liquid manure storages emit greenhouse gases (GHGs) and ammonia (NH3), which can have negative effects in the atmosphere and ecosystems. Installing a floating cover on liquid manure storages is one approach for reducing emissions. In this study, a permeable synthetic cover (Biocap) was tested continuously for 165-d (undisturbed storage + 3-d agitation) in Nova Scotia, Canada. Covers were installed on three tanks of batch-loaded dairy manure (1.3 m depth 6.6 m2 each), while three identical tanks remained uncovered (controls). Fluxes were measured using steady-state chambers. Methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) were measured by absorption spectroscopy, and NH3 was measured using acid traps. Results showed covered tanks consistently reduced NH3 fluxes by approximately 90%, even though a surface crust formed on controls after about 50 days. Covers continued to reduce NH3 flux during agitation. Covered tanks also emitted significantly less CO2 and N2O than the controls (p-value <0.01). However, CH4 fluxes were not reduced, and therefore overall GHG fluxes were not substantially reduced. Short-term trends in CH4, CO2, and N2O flux provided insight into cover function. Notably, bubble fluxes were a key component of CH4 emissions in both treatments, suggesting the covers did not impede CH4 transport.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".