An updated seismic shothole drillers' log-based assessment of potential granular aggregate resources and bedrock outcrop and subcrop occurrences, Ka'a'gee Tu Candidate Protected area, southern Northwest Territories
Bibliographic record
Abstract
This publication's purpose is to provide information on the location and thickness of potential granular aggregate resources (gravel and sand) and bedrock outcrop/subcrop localities which may host suitable quarry material in the vicinity of the Ka'a'gee Tu Candidate Protected Area, southern Northwest Territories. Newly acquired archival seismic shothole drillers-log data from Shell Canada, ConocoPhillips Canada, and Paramount Resources, are used to update previous reconstructions of potential granular aggregate deposits (Open File 6058) and bedrock outcrop/subcrop occurrences (Open File 6410). A total of 713 potential granular aggregate deposits and 4264 bedrock outcrop/subcrop occurrences have been added to the thematic GIS which is presented here. Application of this information is considered beneficial to all manner of regional, community, and resource infrastructure development, and may be incorporated into decision making by those planning the geographical extents and limitations to development in the proposed Ka'a'gee Tu Candidate Protected Area.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".