Developing a collaborative permafrost research program: The Dempster - Inuvik to Tuktoyaktuk highway research corridor, Northwest Territories, Canada
Bibliographic record
Abstract
The Beaufort Delta region in Northwest Territories, Canada is one of the most rapidly warming areas on Earth. Permafrost thaw and climate change are major stressors on northern infrastructure, particularly in this region which hosts the highest density of Arctic communities and the longest road network constructed on ice-rich permafrost in Canada. The Dempster and Inuvik to Tuktoyaktuk Highways (ITH) comprise a 400-km corridor connecting the region with southern Canada. The corridor delivers a unique opportunity to develop a societally-relevant, northern-driven permafrost research network to encourage collaboration, and support pure and applied studies that engage stakeholders, encourage community participation, and acknowledge northern interests. Successful implementation requires leadership and institutional support from the Government of the Northwest Territories (GNWT) and Inuvialuit and Gwich’in Boards and landowners, and coordination between research organizations including NWT Geological Survey, Aurora Research Institute, Geological Survey of Canada, and universities to define key research priorities, human and financial resources to undertake studies, and protocols to manage data collection and reporting. In 2017, a state of the art ground temperature monitoring network was established along the Dempster-ITH corridor by the GNWT in collaboration with Federal and Academic partners. This network in combination with the maintenance of the Dempster Highway and recent design and construction of the ITH, has created a national legacy of permafrost geotechnical, terrain and geohazard information in this region. The objectives of this program are to integrate old and new data to synthesize physiographic, hydrological, thermal, and geotechnical conditions along the corridor, and to develop applied permafrost research projects that support planning and maintenance of this critical northern infrastructure. In this presentation, we highlight: 1) a collaborative research framework that builds northern capacity and involves northerners in the generation of knowledge and its application to increase community based permafrost monitoring; 2) summaries of existing infrastructure datasets and their foundation for research; and 3) new projects that address emerging climate-driven infrastructure stressors. As the effects of climate change on permafrost environments, infrastructure and communities continue to increase, the need for northern scientific capacity and applied research to support informed decision-making, climate change adaptation and risk management will become increasingly critical. The development of resilient researcher-stakeholder-community relationships is also necessary for the scientific and research initiatives to reach their potential.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".