Bibliographic record
Abstract
The Climate Change Geoscience Program (CCG) at the Earth Science Sector (ESS) contributes to adapting to environmental impacts from climate change through the provision of critical earth science information to support policy and regulation decisions. The interaction between the development of a scientific knowledge base and the development of appropriate policy decisions is fundamental to achieving meaningful outcomes. The program's fundamental role lies in providing a suitable base of geoscience knowledge, accomplished by identifying the knowledge needs and gaps through collaboration with stakeholders. Specifically the geoscience in the CCG Program focuses on those environmental variables that will be most impacted and altered by a changing climate namely the cryosphere (permafrost, glaciers and snow cover), water (availability trends and impacts as well as water level changes) and vulnerable landscapes (particularly coastal areas and northern ecosystems). Significant changes to these components of the environment will affect Canadians, their prosperity and ability to benefit from their environment. Scientific activities will quantify the environmental impacts using leading edge techniques that provide excellent knowledge and predictive insights. The scientific knowledge base is being delivered through a mix of earth observation, both remote and in-situ, and quantitative assessments of landscape and ecosystem response. Projects are multi-disciplinary respecting the multi-dimensionality of environmental issues and the need to study the interaction between variables. Northern vulnerability is particularly highlighted in the program as evidence for more rapid climate change and accelerating impacts in northern Canada has been cited as a critical driver in the government's Northern Strategy which also recognizes environmental degradation, vulnerable infrastructure, and transportation as areas requiring attention. The outcome will be achieved through engagement in the current round of national and international assessments, in particular through the Intergovernmental Panel on Climate Change (IPCC) as well as the International Polar Year (IPY).
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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; both teacher heads agree on what is shown here.
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".