Status of surficial geology mapping in northern Canada
Bibliographic record
Abstract
The Geo-mapping for Energy and Minerals (GEM) program has facilitated the availability of new and converted surficial geology maps and associated digital data sets for large sectors of northern Canada, leading to about 70% of the North being mapped and digitally available. Development of the Surficial Data Model and Canadian Geoscience Map (CGM) series has streamlined the publication process and created a common standard digital-map format and geodatabase. Based on traditional and more recent remote predictive mapping methodologies, there are now three types of surficial geology CGM maps produced: surficial geology, reconnaissance surficial geology, and predictive surficial geology. The considerable number of new surficial geology maps published during the two phases of the GEM program, as well as upcoming map publications, has resulted in an increase of 12% in map coverage north of 60°, constituting a significant legacy of the GEM program.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".