Bibliographic record
Abstract
This study investigates the 3C-3D surface and downhole (VSP) seismic datasets previously collected at the Athabasca Basin McArthur River to Millennium uranium mine sites using a number of unconventional analytical methods. The objective is to understand the potential of the seismic method to delineate subsurface features such as the hydrothermal alteration footprint, the sandstone-basement unconformity and the subvertical thrust fault zone. Methodologies applied include a series of forward and data-driven approaches. First, this study accomplishes the prediction of the compressional and shear wave amplitude and traveltime using angle dependent reflectivity equations and 2D elastic finite-difference waveform models. The numerical predictions are based on the existing and estimated petrophysical data from the local area. Second, this study discovers a number of unique properties of the seismic wave attenuation from surface and downhole seismic datasets. Multiple methods applied to VSP datasets confirm that the attenuation quality factor (Q) in the study area is low and variable. Finally, this study analyzes the traveltime and waveform data collected from the unique 3C-3D-borehole seismic geometry at Millennium to delineate the subsurface geologic structures that are potentially related to the wave attenuation and velocity. A forward 3D visco-elastic waveform model is created to illustrate the observed abnormal amplitude and velocity azimuthal variations with a superimposed effect of intrinsic and scattering. The results from these series of approaches provide updated understandings of the alterations, structural geology, and their relationships with seismic data. These understandings contribute to the suggestions for future seismic imaging work such as converted shear wave processing, downhole seismic acquisition, and alteration footprint tomography.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 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".