Palsa and peat plateau development in the Hudson Bay Lowlands, Canada: timing, pathways and causes
Bibliographic record
Abstract
The Holocene development of a treed palsa bog and a peat plateau bog, located near the railroad to Churchill in the Hudson Bay Lowlands of northeastern Manitoba, was traced using peat macrofossil and radiocarbon analyses. Both sites first developed as wet rich fens through paludification of forested uplands around 6800 cal. yr BP. Results show a 20th‐century age for the palsa formation and repeated periods of permafrost aggradation and collapse at the peat plateau site during the late Holocene. This timing of permafrost dynamics corroborates well with that inferred from previous studies on other permafrost peatlands in the same region. The developmental history of the palsa and peat plateau bogs is similar to that of adjacent permafrost‐free fens, except for the specific frost heave and collapse features associated with permafrost dynamics. Permafrost aggradation and degradation is ascribed to regional climatic, local autogenic and other factors. Particularly the very recent palsa development can be assessed in terms of climatic changes as inferred from meteorological data and surface hydrological changes related to construction of the railroad. The results indicate that cold years with limited snowfall as well as altered drainage patterns associated with infrastructure development may have contributed to the recent palsa formation.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".