3D diffraction and mode-converted scattering signatures of base metal deposits, Bathurst Mining Camp, Canada
Bibliographic record
Abstract
The localized and isolated nature of base-metal deposits can generate a complex scattered wavefield that may include P-P, P-S, S-P, and S-S events. Multi-component VSP data have previously confirmed the presence of several wave types scattered by a deep-seated base metal deposit at Halfmile Lake, Bathurst Mining Camp, Canada. However, mode-converted waves scattered from a massive sulphide deposit have not previously been recognized on surface seismic data. In this study, we used 3D surface seismic data acquired with an explosive source and vertical geophones to investigate the possible presence of P-P, P-S, S-P, and S-S events scattered at a base metal, lens-shaped body at about 1.2 km depth. We show that this body produces a diagnostic P-P diffraction and use finite-difference modelling to show it could produce mode-converted scattered signals. Results from a target-oriented azimuthal scattering analysis based on 3D prestack migration reveal amplitude anomalies at the location of the base metal lens for S-P waves and possibly P-S waves. The identification of these events confirms that mode-converted waves scattered from the deep sulphide lens were recorded on the 3D data. However, the real potential of these complementary wave modes for mineral exploration will only be realistically evaluated using P- and S-wave sources and multi-component receivers.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".