Wood‐Based Carbon Storage in the Mackenzie River Delta: The World's Largest Mapped Riverine Wood Deposit
Bibliographic record
Abstract
Abstract The Mackenzie River Delta (MRD) has been recognized as an important host of river‐derived wood deposits, and Mackenzie River wood has been found across the Arctic Ocean. Nevertheless, we lack estimates of the amount of carbon stored as wood and its age in the delta, representing a gap in carbon cycle estimates. Here, we use very high‐resolution satellite imagery and deep learning to map wood deposits in the MRD, combining this with field data to measure the stock and age of wood‐based carbon. We find >400,000 individual large wood deposits, collectively storing 3.1 × 10 12 g‐C, equating to 2 × 10 6 g‐C ha −1 across the delta. Sampled wood pieces date from 690 AD to 2015 AD but are mostly young with ∼40% of the wood samples formed after 1955 AD. These estimates represent a minimum bound on an important surficial, potentially reactive, carbon pool compared to other deeper carbon stocks in permafrost zones.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".