Can Analysis of Historic Lagg Forms Be of Use in the Restoration of Highly Altered Raised Bogs? Examples from Burns Bog, British Columbia
Bibliographic record
Abstract
Natural bogs are generally surrounded by a zone of hydrologic, hydrochemical, and ecological gradients called a lagg. In laggs, large changes over short lateral distances result in distinctive ecological gradients and vegetation patterns. Part of the restoration planning challenge for Burns Bog involves recreating such water and chemistry gradients to establish and maintain conditions for appropriate plant and animal communities that reflect natural transitions from nutrient-poor bog to adjacent mineral-soil-influenced wetlands. We present a conceptual model inferred from historic air photos and vegetation maps from the margins of Burns Bog and theorize how particular vegetation represents the hydrological and hydrochemical gradients of the past that existed in transition to surrounding landscapes. Understanding lagg ecosystems and how they function is important not only to restoring the ecological integrity of Burns Bog, but also to developing a conceptual model useful for predicting and interpreting these gradients in other peatlands.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 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".