Bibliographic record
Abstract
This Open File summarizes ground ice information from 31 sites across the permafrost regions in Canada. The poster presents a map with photographs from each site, and estimates of ground ice abundance from segregated, wedge, and relict ice in top 5 m of permafrost, derived from national-scale mapping by O'Neill et al. (2019; 2020). The sites represent a range of environmental conditions (climate, surficial geology, geological history, vegetation) spanning the continuous and discontinuous permafrost zones in Canada. The report in the Open File provides detailed site descriptions, comments on the modelled ground ice abundance compared to observations of ground ice from the area, the implications of ground ice conditions for thaw processes (thermokarst), and references to key literature. The atlas illustrates the varied ground ice conditions in northern Canada and the associated environmental conditions that control ice type and abundance. Furthermore, the atlas serves as a means to validate and improve recent national-scale ground ice mapping by identifying conditions not well represented by the modelling. This validation has highlighted that an updated national surficial geology dataset that incorporates the latest large-scale GSC mapping would improve the model outputs in many areas by more accurately depicting the distribution of frost-susceptible sediments.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.021 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.062 | 0.019 |
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".