The impact of spatially varying wetland source signatures on the atmospheric variability of dD-CH4
Bibliographic record
Abstract
We present the first spatially varying map of the δD-CH4 signature of wetland methane emissions and model its impact on atmospheric δD-CH4. The δD-CH4 signature map is derived by relating the δD-H2O of precipitation to the measured δD-CH4 of methane wetland emissions at a variety of wetland types and locations. Since the δD-H2O of precipitation is highly latitude-dependent, including this spatial variation has the potential to have a large impact on the distribution of δD-CH4 observed in the atmosphere. This latitude-dependence means that wetland emissions at different latitudes can have very different impacts on atmospheric δD-CH4, which could provide a useful way to constrain the location of wetland methane emissions in future inverse modelling studies. Here, we assess the implications for model studies on the differences that arise by treating δD-CH4 wetland source signatures as globally uniform rather than accounting for the large spatial variation. We also assess the potential for δD-CH4 to provide an independent constraint on wetland emissions over the more abundant and widely measured δ13C-CH4.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".