GEM-Mackenzie: bedrock mapping and related stratigraphic studies, 2009-2019
Bibliographic record
Abstract
The Geo-mapping for Energy and Minerals (GEM) Program provided an opportunity to update the state of bedrock geological mapping for nearly 92,000 km2 of the northern mainland Northwest Territories, in a swath extending from the Colville Hills and Great Bear Plain, westward to the eastern and northern Mackenzie Mountains. Mapping focused initially on the region around the long-producing Norman Wells oil field, and subsequently extended north to the Colville Hills, a region of known oil and gas potential, and west into the Mackenzie Mountains, an area with numerous mineral showings. The result will be 24 new bedrock geology maps at 1:100 000 or 1:250 000 scales, published in GIS-enabled format as Canadian Geoscience Maps (CGMs). The mapping effort made extensive use of archival GSC data, notably those preserved following Operation Norman (1968-1970), as well as public-domain industry data. Maps incorporate numerous stratigraphic revisions that post-date the Operation Norman era, including innovations from the GEM program that affect a number of Tonian, Ediacaran, Cambrian, and Ordovician units. The present report is an overview of the mapping efforts, including summaries of stratigraphic revisions, as well as a preliminary treatment of the structural geology of the study area. Also included is a brief summary of subsurface studies. Following the conclusion of the GEM program, modern, GIS-enabled bedrock maps will be available for a swath of territory extending from the edge of the Selwyn Basin, near the Yukon border, to the Brock Inlier in the northeastern mainland Northwest Territories.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".