Controls on carbon dioxide and methane fluxes from a low-center polygonal peatland in the Mackenzie River Delta, Northwest Territories
Bibliographic record
Abstract
Growing season surface–atmosphere exchange of carbon dioxide and methane were quantified at Fish Island, a wetland site in the lower northeast Mackenzie River Delta, Northwest Territories, Canada. The terrain consists of low-center polygonal tundra and is subject to infrequent flooding in high water years. Carbon dioxide and methane fluxes were continuously measured using eddy covariance and the relevance of different environmental controls were identified using neural networks. Net daily carbon dioxide uptake peaked in mid-July before gradually decreasing and transitioning to net daily emissions by September. Variations in light level and temperature were the main controls over diurnal net carbon dioxide uptake, whereas thaw depth and phenology were the main seasonal controls. Methane emissions measured at Fish Island were higher than comparable studies on river delta sites in the Arctic and were influenced by the interaction of a large number of factors including thaw and water table depth, soil temperatures, and net radiation. Spikes in methane emissions were associated with strong winds and turbulence. The Fish Island tundra was a net sink for carbon during the growing season and methane emissions only slightly reduced the overall sink strength.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".