73 Within and between animal variation in supplement intake with the use of a novel precision feeding system for beef cattle
Bibliographic record
Abstract
Abstract Survey data suggests that in Western Canada, approximately 62% of forage samples may not meet energy requirements for gestating beef cows in 2nd trimester of pregnancy. Individual supplementation via a precision feeder would improve animal productivity and welfare. A CV of 30% was selected as a threshold for acceptable variation based on previous studies, which reported a CV of 41% for supplements hand-fed to grazing animals. Over three, 14-d experimental periods, precision feeders were used to deliver and monitor consumption of the following supplements to 24 steers (375 kg; n = 8 per pen): 1) supplementation of low protein forage (5.5% CP) with commercial pellets (1 kg hd-1d-1 with and without flavoring); 2) supplementation of low protein forage (5.5% CP) with processed pea screening powder (PPSP), sunflower screenings, and flax screenings provided at 0.57, 1.04, and 1.34 kg hd-1d-1, respectively; and 3) supplementation of low energy forage (41.4% TDN) with wheat screenings, wheat bran, and quinoa dockage all provided at 2.61 kg hd-1d-1. Feeding commercial pellets without flavoring resulted in within animal CVs (15.12% and 13.15%) and between animal CVs (14.78% and 12.68%) similar to pellets with flavoring (13.98% within and 12.85% between animal CV). Steers offered PPSP had significantly higher within and between animal CV (31.05% and 31.41%, respectively) than was observed for animals offered sunflower screenings (14.98% within and 18.30% between animal) and flax screenings (11.19% within and 16.03% between animal). Within and between animal CV was 6.99% and 7.14% for wheat screenings, 10.47% and 11.77% for wheat bran, and 10.07% and 10.42% for quinoa dockage. Intake CV for all supplements was below 30% except for PPSP which may have resulted from the powdery texture or low amount offered relative to other feedstuffs, indicating that the precision feeders are an effective system to deliver supplements on an individual animal basis.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".