Bibliographic record
Abstract
Extraction of oil from the Alberta Oil Sands through surface mining involves the removal of the overburden and oil sand to a depth of up to 100 m and over extremely large areas. While the operation of the bitumen processing plants has serious environmental impacts on downstream habitats, this article focuses on the reclamation of areas from which the oil sands have been removed, processed, and returned. This reclamation following closure of the mines will entail the complete re-creation of landforms and ecosystems at a landscape scale, with the goal of producing suitable habitats for plants, animals, and people. Such projects will require a reasonable understanding of the geophysical and ecological processes that operate at a wide range of scales. Some information is provided on the climate, hydrology, vegetation, and land use (past and current) of the Oil Sands area, situated within the Boreal Plain ecozone, to provide a framework for discussion of issues to be addressed in, and proposed guidelines for, such large-scale reclamation. Although none of the mines has yet closed, numerous consultant reports have been produced with recommendations for various aspects of such reclamation projects (e.g., wetland hydrology, vegetation, wildlife habitat). The scientific basis of such reports is found to vary with respect to depth of understanding of the relevant processes.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".