1704 Factors influencing estimates of energy used for activity by grazing meat goats
Bibliographic record
Abstract
Ten yearling Boer goat wethers (45.4 ± 0.92 kg) consuming fresh Sudangrass ad libitum while grazing (GRA) a 0.8-ha pasture or individually confined (CON) were used in a crossover experiment with 3-wk periods to evaluate factors influencing estimates of energy used for activity (AEC) when grazing. Fresh forage offered to CON wethers was 15.9 and 13.4% CP and 65.0 and 67.4% NDF in periods 1 and 2, respectively. Based on forage and fecal AIA, forage DE concentration for CON averaged 67.9 and 56.5% in periods 1 and 2, respectively. From these values and fecal DM, least squares means of ME intake were 405 and 484 kJ/kg BW0.75 for CON and GRA, respectively (SE = 15.4). Heat energy (HE) determined from heart rate (HR) measured over 1 d and the ratio of HE to HR estimated earlier was less (P < 0.001) for CON than for GRA (482 and 642 kJ/kg BW0.75; SE = 17.2). To estimate the AEC from total HE and the partitioning of its sources, a ME requirement for maintenance of 427 kJ/kg BW0.75) was assumed; HE expended for tissue energy gain was determined from recovered energy (RE) when greater than 0 and an efficiency of ME use for gain of 0.40 ± 0.009 ([0.0423 × forage ME in MJ/kg DM] + 0.006); and, when RE was less than 0, the efficiency of use for maintenance of energy from forage and mobilized tissue was 0.68 ± 0.004 ([0.019 × forage ME in MJ/kg DM] + 0.503). The resultant AEC was 39 and 213 kJ/kg BW0.75 for CON and GRA, respectively (SE = 21.9). Assuming that mobilized tissue energy was used for maintenance more efficiently (i.e., 0.80) than forage ME yielded slightly greater AEC of 57 and 241 kJ/kg BW0.75 for CON and GRA, respectively (SE = 23.9). The former AEC value for GRA and that determined from the difference between GRA and CON HE were much greater than AEC based on time spent in different activities (i.e., lying, standing, grazing, and walking) multiplied by corresponding HE and assuming that AEC resulted from HE when standing, grazing, and walking (217 ± 19.7, 165 ± 19.3, and 46 ± 4.85 kJ/kg BW0.75, respectively). In conclusion, determining the AEC of meat goats while grazing by subtraction of other sources of HE is influenced by specific assumptions of energy requirements and efficiencies of use for different physiological functions.
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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) | 0.001 | 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".