NUTRITIONAL EFFECTS OF HOUSEHOLD FOOD WASTES SUPPLEMENTATION IN SHEEP DIET
Bibliographic record
Abstract
The present study aimed to assess the household food waste (HFW) as a substituted source of low cost feed for sheep. HFW was freshly collected, weighed, dried, ground and then chemically analyzed. On as-fed basis, HFW was used as an ingredient in the formulating balanced diet for lambs at varying levels of substitution (0 %, 15 % and 30%). On dry matter (DM) basis, HFW contained moderate protein content (14.72%), ether extract (6.96%), non-fibrous carbohydrate (47.39%), and ash (10.98%). The growth performance and feed efficiency of lambs supplemented with 15 and 30% HFW-contained diets were similar to control animals. The effect of HFW on fasted live weight, carcass weight, dressing percentages and meat chemical composition was also within the range of lambs feed on normal diet. Histopathologically, mosaic appearance of glycogen infiltration which may support the fattening effect. Unless, the oval cell proliferation associated with higher serum levels of GGT enzyme in 30% HFW-containing diet, which might be attributed to higher residue levels of iron in HFW. Therefore, HFW might be incorporated in lower concentration in lamb diet.
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 | 0.000 | 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".