Energy utilization in cattle with steady state and non-steady state methods: the importance of thermal neutrality
Bibliographic record
Abstract
The efficiency by which animals utilize dietary energy is fundamental to the cost of production for protein of animal origin and to the carbon footprint an animal industry has. Hence, the development of cost effective methodology for determining these measurements of efficiency is important. The objective of the present study was to investigate the use of infrared thermography in a rapid, non-steady state method for measuring energy loss in cattle. Data from 241 yearling bulls and steers as well as heifers and mature cows are presented. Infrared images were collected following a 24h feed withdrawal period. The infrared thermal response in these animals was significantly ranked (P < 0.03) with conventional measurements of feed efficiency using residual feed intake values for animals demonstrated to be within a thermal neutral zone. When animals were not within a thermal neutral zone there was no significant ranking. The data suggests that the use of a non-steady state approach using infrared thermography for identifying metabolic efficiency in animals may be a more rapid and less expensive method for identifying differences in energy utilization. The data also demonstrates the importance of maintaining thermal neutrality when measuring metabolic efficiency irrespective of the methodology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".