Tracing the footprint of permafrost carbon supply to the Canadian Beaufort Sea
Bibliographic record
Abstract
The Canadian Beaufort Sea receives large quantities of sediment, organic carbon and nutrients from rapid coastal erosion and permafrost degradation. In addition, the Mackenzie River, the largest North American Arctic river, discharges great amounts of freshwater, dissolved solids and suspended sediments to the Beaufort Sea. Current changes in these fluxes in response to the warming climate have uncertain consequences for the carbon budget on the shelf and in the deep ocean. To investigate the movement and transformation of organic matter along the land-ocean continuum, we collected water and surface sediment samples along five major transects across the Beaufort Sea during the 2021 expedition of the Canadian Coast Guard Ship Amundsen. Sampling locations span from shallow, coastal, sites with water depths ≤ 20 m, to shelf-break and deep-water settings on the continental slope (water depths of ≥1000 m). For this study, we use stable and radiocarbon isotopic (δ13C and Δ14C) analyses of dissolved inorganic (DIC), dissolved organic (DOC) and particulate organic carbon (POC) for surface and bottom waters, as well as surface sediments, in order to compare, contrast and constrain the relative source contributions and ages of these different forms of carbon. Our results will help to better understand the fate of permafrost organic matter in the marine environment and to ultimately improve assessments of the Canadian Beaufort Sea shelf as a carbon source or sink and its potential trajectory with ongoing environmental changes.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".