Bibliographic record
Abstract
The poultry industry is one of the largest and fastest growing sectors of livestock production in the world. The estimated 2010 world flock was over 18 billion birds with a yearly manure output of 22 million tonnes. Storage and disposal of raw poultry manure have become an environmental problem because of the associated air, water and soil pollution. Environmental and health problems such as odor and pathogens that may arise during and after land application of raw manure can be eliminated by drying. Dried manure can be utilized as a feed for ruminants because of its high nitrogen content. The aim of this study was to investigate the effects of drying temperature and depth, as well as the nutritional profile of dried manure and its suitability as an animal feed. Dried poultry manure contained sufficient levels of digestible energy, crude fiber, crude protein, crude fat, cobalt and iodine. Although dried poultry manure did not meet the dietary requirements for calcium, chloride, magnesium, phosphorus, potassium, sodium, copper, iron, manganese, selenium, sulfur or zinc it could be used as a feed stuff for ruminants after supplementation with the required nutrients. Heated air drying was most efficient at 60°C and at a depth of 3 cm. During drying poultry manure decreased in pH (8.4-6.9), protein content (43 to 39-43%) and amino acid content. The greatest reductions in microbial population occurred at the highest temperature (60°C) and the lowest manure depth (1cm). Reductions in the number of bacteria, mold/yeast and E. coli were 65-99, 74-99 and 99.97% respectively, Salmonellae was not detected in the dried product. Dried poultry manure was found to have a non-offensive odor. Odor intensity and offensiveness were reduced by 65 and 69% respectively during drying. Thin layer heated air drying of poultry manure between 40 and 60°C created a safe and nutritionally appropriate feed for ruminants.
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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".