Correlations of methane and carbon dioxide concentrations from feedlot cattle as a predictor of methane emissions
Bibliographic record
Abstract
Accurate measurements of methane (CH4) emissions from feedlot cattle are required for verifying greenhouse gas (GHG) accounting and mitigation strategies. We investigate a new method for estimating CH4 emissions by examining the correlation between CH4 and carbon dioxide (CO2) concentrations from two beef cattle feedlots in Australia representing southern temperate and northern subtropical locations. Concentrations of CH4 and CO2 were measured at the two feedlots during summer and winter, using open-path Fourier transform infrared spectroscopy. There was a strong correlation for the concentrations above background of CH4 and CO2 with concentration ratios of 0.008 to 0.044 ppm/ppm (R2 >0.90). The CH4/CO2 concentration ratio varied with animal diet and ambient temperature. The CH4/CO2 concentration ratio provides an alternative method to estimate CH4 emissions from feedlots when combined with CO2 production derived from metabolisable energy or heat production.
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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 | 0.002 |
| 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".