Bibliographic record
Abstract
Peatland communities in western Canada have slowly developed over thousands of years with wildfires being a constant influence on these systems. As fires move through mature peatland communities, the aftermath is an open landscape where pioneer peatland species establish and develop. The open landscape supports the growth of successional species to create a mature forest, which is then ready for the fire interval cycle to continue. Fire cycles have been a constant on the landscape with little disruption; however, as climate change in western Canada has altered precipitation and temperature regimes, typical vegetation succession patterns that establish after peatland fires may be changing. The Chisholm fire of 2001 burned over 116,000 hectares of forest in northern Alberta, with most of the area being peatlands (treed fens). Vegetation surveys were completed throughout 2018 and 2019 within the burned peatlands of the Chisholm area and compared to an unburnt control area to identify species richness, diversity, composition and vegetation trends. I found, within the re-establishing peatland, a healthy, thriving and diverse community that is developing towards a community similar to the offsite mature treed fen. After almost 20 years of recovery, the affected vegetation community is dominated by peatland species. With temperatures and precipitation levels continually changing, the area is at a transition state in which the community may be maintained on the landscape or the area may experience a regime shift to a drier state.
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 | 0.001 |
| 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 | 0.001 | 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".