3D Seismic Surveying in Kevitsa Open Pit Mine
Bibliographic record
Abstract
Summary3D reflection seismic survey was conducted over an area of about 9 km2 at the Kevitsa Ni-Cu-PGE (platinum group elements) deposit, northern Finland. About 1000 active receivers and 3000 shots in nine overlapping swaths were used to acquire the data. The principal objective of the survey was to image major fault and fracture zones at depth. Understanding the geometry of these zones is important for designing a steep open-pit for mining. Geological structures are complex and a varying thickness of overburden combined with various weather conditions during the data acquisition pose the data processing very challenging. However, a careful processing design combined with our experience on this type of data helped to produce interesting results. Processing results suggest that the 3D seismic survey has been successful in imaging both gently dipping and steeply dipping reflections as shallow as about 150 m, many of which correlate with fault systems and lithological contacts observed at the surface. Several new target areas, bright spots, are identified in the seismic data that require further investigations for their mineralization potential.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".