Peat Depth and Carbon Storage of the Hudson Bay Lowlands, Canada
Bibliographic record
Abstract
Abstract The Hudson Bay Lowlands (HBL) are recognized as the second largest peatland complex in the world. Due to variability in peat thickness across a large and heterogeneous landscape, the existing carbon (C) storage estimates for the HBL may contain large uncertainty. Here, we use geospatial variables that are associated with HBL peat formation, age, accumulation, and occurrence to understand the driving factors for peat depth variability and map peat depth and C storage at 30 m spatial resolution. The estimated average peat depth of HBL is 184(±48) cm with 90% of values falling between 89 and 264 cm. Based on the spatially explicit peat depth, the HBL total C storage is estimated to be 30(±6) Pg. Distance to the coastline is the most important indicator of peat depth where the depth increases with distance further away from Hudson Bay coastline, confirming that the time since peat formation is closely related to peat depth.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".