3D seismic reflection imaging of volcanic-hosted massive sulfide deposits: Insights from reprocessing Halfmile Lake data, New Brunswick, Canada
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Bibliographic record
Abstract
Abstract Three-dimensional seismic reflection data from the Halfmile Lake area, New Brunswick, Canada, was reprocessed over an 18- km2 grid to improve the seismic signatures of a 5-million-ton volcanic-hosted massive sulfide (VHMS) deposit located at 1200-m depth, known as the deep zone, as well as key host-rock structures. We chose a prestack dip moveout (DMO) and poststack migration processing sequence to preserve the possible diffraction signature of the deep VHMS zone. Despite the high level of source-generated noise and large statics caused by near-surface conditions, our processing results revealed improved 3D seismic images for shallow and deep structures. Many of the imaged structures were easily correlated with known lithological con-tacts constrained by boreholes and petrophysical measurements. A short, flat-lying segment of high-amplitude reflection at about 800-m depth in the unmigrated cube was interpreted to originate from a small portion of the lower VHMS zone. The DMO stack was characterized by a large, high-amplitude asymmetric diffraction signature originating from the deep VHMS zone. The asymmetry of the diffraction hyperbola relative to the location of the deep zone was interpreted as resulting from a shape effect from the zone, with the strongest amplitudes along the diffraction hyperbola found north-northwest of the apex. This indicated that the deep VHMS zone dips in a similar direction. This diagnostic diffraction signature was not preserved with the prestack migration approach previously implemented for processing Halfmile Lake data.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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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 it