Odour emission rates from manure treatment/storage systems
Bibliographic record
Abstract
The effects of agitation, liquid-only manure, depth and time on odour emission rates were investigated. Manure storage tanks were filled to incremental depths every two weeks. At each depth odour samples were collected twice. The second sample was collected seven days after the first. Odour concentration was measured with an olfactometer. Three different pig-manure treatments were investigated. In one treatment, slurry manure in a storage tank was agitated before and during odour sampling. In a second treatment, the settlable solids in manure were removed gravimetrically over 24 hours and liquid manure was pumped to a storage tank. In the third treatment (control), odour samples were collected from unseparated and undisturbed slurry manure. Overall, the odour emission rates in the agitated manure treatment ranged between 0.39 and 1.02 ou s(-1) m(-2), increased with depth and decreased with time, i.e. after seven days at each depth. In the liquid-only manure treatment, the emission rates ranged between 0.09 and 0.69 ou s(-1) m(-2), increased with depth but the effect of time was not evident. In the control treatment, the emission rates ranged between 0.20 and 0.66 ou s(-1) m(-2) and increased with depth on the first odour sampling day but decreased with depth on the second sampling day.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".