Reestablishment of peatland vegetation following surface leveling of decommissioned in situ oil mining infrastructures
Bibliographic record
Abstract
Peatland ecosystem restoration following oil mining activities in Alberta, Canada, aims at reestablishing crucial peatland functions, such as wildlife habitat, water storage and filtration, peat accumulation, and carbon sequestration. To reinstate peatland functions, characteristic hydrological conditions are necessary to support the establishment and growth of characteristic wetland vegetation. Following in situ oil sands well pad disturbances in the Peace River and Cold Lake Oil Sands regions in Alberta, we evaluated the efficiency of peatland restoration approaches including different groundwork and revegetation techniques. Groundwork techniques included the complete removal (CR) or partial removal (PR) of the former in situ well pads' mineral fill and revegetation included the spontaneous revegetation via natural ingress of diaspores from nearby peatlands, or managed revegetation via planting of Carex aquatilis, Larix laricina, and Salix lutea. We assessed the plant species composition, biochemical and hydrological properties of all study areas, including restored peatland areas, an unrestored area, and reference areas (REF) for comparison. Ten years post‐restoration, in the restored areas the mean total plant cover was 57% with an average of 35 vascular plant and bryophyte species, while in REF 68% mean total plant cover and an average of 64 plant species were recorded. Respectively, characteristic peatland species contributed to 61 and 100% of the species composition. PR and hydrological connection to the adjacent peatland resulted in near surface water table and the highest peatland plant species diversity, while CR promoted the formation of a shallow open water area.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".