Application of modern 2-D and 3-D seismic-reflection techniques for uranium exploration in the Athabasca BasinThis article is one of a series of papers published in this Special Issue on the theme<i>Lithoprobe — parameters, processes, and the evolution of a continent</i>.
Bibliographic record
Abstract
Seismic-reflection techniques have been applied in several studies over the last 20 years as a uranium-exploration tool within the Athabasca Basin and have been utilized to provide the larger structural context for known uranium deposits within the basin. At the crustal scale, deposits within the eastern Athabasca Basin are shown to be associated with deep-seated shear zones that originated during Trans-Hudson orogeny and have subsequently been reactivated during and subsequent to deposition of the basin-fill sandstones. Seismic properties of the Athabasca sandstones and underlying basement have been determined through in situ borehole measurements. Reflectivity within the sandstones is generally weak. Seismically recognizable signatures are primarily associated with variations in fracture density, porosity, and degree of silicification. The basement unconformity and regolith, a prime target of exploration, is widely imaged as it is characterized by variable but generally distinct reflectivity. Results from the McArthur River mine site suggest that the spatial coincidence of seismically imaged high-velocity zones and deep-seated faults that offset the unconformity may be a more broadly applicable exploration targeting tool. Three-dimensional (3-D) seismic imaging near existing ore zones can define the local structural controls on the mineralization and point the way to new targets, thus leading to more efficient exploration drilling programs. Furthermore, seismically generated structural maps of the unconformity and rock competence properties may play a significant role at the outset of mine planning.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".