Comment on egusphere-2022-549
Bibliographic record
Abstract
Abstract. The Mackenzie River Delta is the second largest Arctic river delta in the world. Thin and destabilizing permafrost coupled with vast natural gas reserves at depth, high organic content soils, and a high proportion of wetlands create a unique ecosystem conducive to high rates of methane production from biogenic and thermogenic sources. Hotspots are known to have a significant contribution to summertime CH4 emissions in the region, but little research has been done to determine how often geologic or biogenic methane contributes to CH4 hotspots in the Mackenzie River Delta. In the present study, stable carbon isotope analysis was used to identify the source of CH4 at several aquatic and terrestrial sites thought to be hotspots of CH4 flux to the atmosphere. Source stable carbon isotope (δ13C-CH4) signatures were derived from keeling plots of point samples and ranged from -42 to -88 ‰ δ13C-CH4, identifying both biogenic and thermogenic and mixed biogenic/thermogenic sources. A CH4 source was determined for eight hotspots, two were thermogenic in origin, four were biogenic in origin, and two were from mixed biogenic/thermogenic sources, as evidenced by δ13C-CH4 signatures. This indicates that the largest hotspots of CH4 production in the Mackenzie River Delta are caused by a variety of sources. In addition to biogenic production at the surface we have identified CH4 migration to the surface from the Taglu gas field over an area of approximately 20 km from north to south and two different sites of mixed biogenic/thermogenic CH4 that were approximately 30 km apart.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.017 | 0.009 |
| Insufficient payload (model declined to judge) | 0.471 | 0.320 |
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".