Mapping the impacts of legacy oil wells and permafrost thaw on vegetation in the Northwest Territories, Canada
Bibliographic record
Abstract
Thawing permafrost increasingly threatens the integrity of legacy sites from resource exploration and extractive industries. In the Northwest Territories, Canada, over 200 sumps containing drilling wastes within permafrost pose considerable environmental and health risks to local ecosystems and populations relying on the land for subsistence. Exploratory drilling activities have caused long-term disturbances to permafrost terrains and tundra vegetation, necessitating continued monitoring and research. This study investigates the complex interactions between legacy oil well disturbances, permafrost thaw, and vegetation changes. Using a combination of field-based and remote sensing techniques, we mapped and assessed the impacts of four drilling mud sumps located along the Inuvik-Tuktoyaktuk Highway (Northwest Territories, Canada). Multispectral drone surveys were conducted at the sites to produce high-resolution orthophotos, digital elevation models, landcover and vegetation index maps. Additionally, we measured the active layer thickness, percent cover of plant functional types, and canopy height within vegetation plots distributed along transects that covered both undisturbed and disturbed terrains. Here, we present preliminary findings from these investigations, including statistical and spatial analyses of the gathered data. Decades after decommissioning, the disturbances caused by the drilling mud sumps, coupled with permafrost degradation processes, continue to affect plant communities, shrub growth and vegetation productivity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".