Repeatability and variability of short-term spot measurement of methane and carbon dioxide emissions from beef cattle using GreenFeed Emissions Monitoring System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: The purpose of this study was to determine the repeatability of methane (CH4) and carbon dioxide (CO2) emissions from beef cattle using GreenFeed emissions monitoring (GEM) system and as affected by sampling frequency and measurement periods. Twenty-eight crossbred replacement beef heifers were monitored using the GEM system over 59 d to collect their CH4 and CO2 emissions data. Heifers’ feed intake was recorded by eight automated feeding stations. The standardized dry matter intake (SDMI), CH4 and CO2 emission and yield (g kg-1 SDMI) were averaged over 1, 3, 7, and 14 d periods. On average, animals emitted 204.7 g d-1 (SD = 36 g d-1) and 6408 g d-1 (SD = 780 g d-1) of CH4 and CO2, respectively. Between-animal coefficients of variation for all variables decreased with an increasing averaging period (from 1 to 14 d). The coefficient of determination (R 2) between CH4 emission and SDMI was increased from 0.25 to 0.73 as averaging period increased from 1 to 14 d. Similarly, the R 2 between CO2 emission and SDMI increased from 0.39 to 0.79 as averaging period increased from 1 to 14 d. It was determined that averaging over 7 to 14 d with minimum of 20 spot samples was needed to produce repeatable and reliable averaged CH4 and CO2 emissions and correlated with SDMI.
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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 | 0.001 | 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 | 0.001 |
| 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 it