Geo-mapping Frontiers: Updated information on the regions covered by Operations Baker, Bathurst, Keewatin, Northern Keewatin, Thelon and Wager; Nunavut and Northwest Territories: National Reference Collection maps and tables, NTS 55 and 56
Bibliographic record
Abstract
The Geo-mapping Frontiers project was initiated to improve geoscience knowledge in the least understood parts of Canada's north. Open File 7434 is part of a series of open files, 7434 to 7448, produced during the Geo-mapping Frontiers project. The series contains legacy geology data and remote predictive mapping information for a large part of eastern mainland Nunavut, collected over 2 years. The derived data products from this work are presented in 15 separate thematic packages to keep the downloads to a manageable size, between 1 and 4 GB. ArcGIS users (version 9.3 and above) can download OF 7434 and any of the georeferenced raster data in the rest of the series. Users not interested in geodatabases will find data in shape files in Open Files 7434 and 7435, or in georeferenced raster data in the rest of the series. This series of publications represents a compilation of available data sets for four regions, and their surrounding areas, that encompass a large part of eastern mainland Nunavut. Several interpretive Remote Predictive Mapping (RPM) layers are included. The data sets include airborne geophysics, LANDSAT 7 imagery, lake sediment analyses, as well as legacy mapping and sample data from the Geological Survey of Canada (GSC) archives. This series is the first of a group of reports for the Geo-mapping Frontiers project, and is intended to provide a basis of knowledge for the entire region.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.019 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.101 | 0.031 |
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".