Bibliographic record
Abstract
Paunch manure, the contents of the rumen of cattle at slaughter, has been largely landfilled in Ontario in recent years. Very few other options have been available for dealing with this material. With the increased costs of landfilling and with pressure to divert materials from landfills, it is important to find alternative means of disposal or use. Because paunch manure has characteristics similar to livestock manure, it should be an ideal material for composting. Previous studies have looked at both anaerobic digestion and composting as means of processing paunch manure. Composting can be a practical, environmentally friendly method to handle this material. Composting offers several environmental benefits. Typically, compost represents an excellent source of nutrients for plant growth, it is free of pathogens and weed seeds and it is free of offensive odours. A trial was carried out in 2004 at Ridgetown College, University of Guelph, to assess the potential to compost paunch manure in a farm scale in-vessel composter. Paunch manure was mixed with solid cattle manure and composted. The composting system is covered and has forced aeration and mechanical turning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.873 | 0.643 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".