Physical, chemical and ecological performance of Syncrude Canada Ltd’s Base Mine Lake
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Base Mine Lake (BML), the first commercial demonstration of water-capped tailings technology (WCTT) in the mineable oil sands in Alberta, Canada, was commissioned in December 2012, following seventeen years of transfer of fine tailings (FT) into West-in-pit. BML’s design basis is that over time, the FT will be physically isolated due to self-weight consolidation, the lake’s water quality will improve, and the lake will ultimately achieve targeted closure outcomes. Since commissioning, the lake has been intensively monitored to track the physical, chemical, and ecological parameters of the FT and the water cap in order to demonstrate the viability of WCTT in reclaiming FT. The FT is consolidating as predicted by finite-strain consolidation theory, reflected by increasingly distinct mudline and profile density increases with time. The water chemistry of BML is improving with decreasing concentrations of many key constituents below both acute and chronic protection of aquatic life guidelines. The lake’s ecosystem is developing, with the establishment of an aquatic invertebrate community. An adaptive management approach helps steward BML towards desired short and long-term objectives. Adaptive management actions have included alum treatment to address water turbidity, and removal of bitumen mats from the FT surface. Improvements observed in the trajectory of the physical, chemical, and ecological parameters for BML are consistent with its short-term objectives. Ongoing monitoring and adaptive management of BML will continue to ensure its long-term closure objectives are met.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it