Evaluation of internal and external markers to estimate faecal output and feed intake in sheep fed fresh forage
Bibliographic record
Abstract
The objectives of the present study were to estimate dry-matter intake and output of faeces using two external and four internal markers in sheep fed Brachiaria brizantha cv. Marandu on an ad libitum basis over 3- and 5-day periods. Six sheep fitted with ruminal cannulas were randomly assigned in a crossover design experiment to receive either of two treatments of external markers, namely titanium dioxide (TiO2) and chromic oxide (Cr2O3). Faecal output was obtained by total faecal collection and faecal grab sampling. Faeces were collected for 3- or 5-day periods, and, for each collection period, two sampling methods were compared; grab samples were collected directly in the rectum once daily, and a second sample was taken at the same time directly in faecal collection bags after having determined the daily total output of faeces. Faecal concentrations of the internal markers, indigestible dry matter, indigestible neutral detergent fibre, indigestible acid detergent fibre and indigestible acid detergent lignin (iADL), were determined. Faecal output was not accurately predicted with indigestible dry matter, indigestible neutral detergent fibre, indigestible acid detergent fibre and iADL. Dry-matter intake was predicted with iADL and TiO2 when faeces were collected for 5 days as grab samples once daily, or as total collection and with Cr2O3 when faecal grab samples were collected for 5 days. The results using external markers indicated that TiO2 is not a marker equivalent to Cr2O3 for estimating intake and faecal output. TiO2 was the only external marker to accurately estimate faecal output, independent of the method (total or grab) and time period (3 or 5 days) used; this suggests that TiO2 is the best marker tested for predicting the faecal output of sheep that are fed a diet of fresh Brachiaria brizantha (cv. Marandu) grass ad libitum.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".