Evaluating spatial variability of free‐phase gas in peat using ground‐penetrating radar and direct measurement
Bibliographic record
Abstract
Several recent studies have estimated that peatlands may have substantial quantities (up to 15–20% by volume) of biogenic free‐phase gas (FPG) below the water table. The presence, distribution, and release of this FPG play important roles in peatland hydrology and biogeochemistry. Despite its importance, investigation of FPG is difficult because most measurement techniques involve disturbance of the peat, potentially altering gas volume in the process. Ground‐penetrating radar (GPR) provides a noninvasive approach to quantify gas content in peat; however, its use for investigating variability in gas content at the microform scale across a peatland and with depth has been limited to date. We investigated variability in subsurface CH4 stock and FPG content between peatland microforms using (1) GPR and the common midpoint method to determine subsurface electromagnetic wave velocity and (2) direct measurement in order to estimate FPG content at three ridges and three hollows in a peatland in northern Alberta, Canada. Higher volumes of FPG were associated with higher CH4 concentrations, suggesting that a reliable estimate of gas volume could also serve as an estimate of stored CH4. In general, both methods found higher volumes of gas under ridges than hollows. When electromagnetic wave velocity was considered, a significant correlation was present with direct measurement of FPG volume. Zones with FPG content up to 20% of peat volume were observed throughout the peat profile including within the upper 1.5 m of peat. Further research is needed to determine physical, chemical, and biological controls on the variability of FPG volume in peat.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".