Bibliographic record
Abstract
Observations have shown that climate is warming, and permafrost is thawing. The major questions now facing us are what are its impacts and consequences, and what can we can do about it. To answer these questions, we need to know more details about permafrost thaw, such as how permafrost will thaw, where, when, and how much. Field observations are essential, but they have limitations in spatial and temporal coverages. Satellite remote sensing (or Earth Observation, EO) can provide detailed spatial information about land surface, and process-based models are important tools for data synthesizing, process understanding, and future projections. EO-based modelling combines these two technologies and can provide spatial distributions and changes based on observations and our understanding. Following this approach, we developed a processbased permafrost model considering the impacts of climate, vegetation, snow, water, soil features and geological conditions. With the inputs of atmospheric climate, vegetation and ground surface conditions from remote sensing, and soil and geological data, we can model ground temperature profiles, active-layer thickness, permafrost conditions, and their spatial distributions and changes with time. We conducted a nation-wide permafrost modelling and mapping study for Canada. The model simulated ground temperature, permafrost distribution, active-layer thickness, and permafrost depth are comparable with observations. The results show that the area underlain by permafrost in Canada will be reduced by 16-20% from the 1990s to the 2090s, and permafrost degradation will continue after the 21st century because the ground thermal regime is in disequilibrium. Now we are working with Parks Canada Agency to model and map permafrost in some northern national parks at a higher spatial resolution. This collaboration not only serves Parks Canada Agency for their monitoring and management operations, but it also provides us a reliable and cost-effective test bed for our methods and results. This EObased permafrost modelling and mapping work has been supported by the climate change program in ESS, a GRIP project, ParkSpace, funded by Canadian Space Agency, and a IPY project, CiCAT.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".