The effect of diet type on residual feed intake and the use of infrared thermography as a method to predict efficiency in beef bulls
Bibliographic record
Abstract
Residual feed intake (RFI) is a recognized measure of biological efficiency in beef cattle. However, RFI determination is expensive, time consuming and not well studied in animals fed forage-based diets. The objectives of this experiment were to investigate infrared thermography (IRT) as method for determining RFI ranking in yearling beef bulls, and to evaluate the effect of diet type on RFI repeatability in consecutive feeding periods. No significant correlations (P > 0.05) were observed between eye or cheek surface temperatures measured using handheld or within-pen stationary infrared camera systems with RFI. Reranking was observed for RFI in all diet treatments, however significant repeatability estimates occurred for the forage and grain diet treatments (r=0.58 and 0.64 respectively; P < 0.01) but not the diet switch treatment (r=0.24; P > 0.05). Extreme cold temperatures experienced in Western Canada influence IRT measurements and energy partitioning, indicating the need for standardized performance testing procedures.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".