Recovery and analysis of historical mine data in a three-dimensional environment: A case study - Heath Steele, Bathurst Mining Camp, northern New Brunswick
Bibliographic record
Abstract
3-D geographic information systems (GIS) provides a powerful tool for visualizing and interpreting the subsurface distribution of geology and hydrothermal parameters that are important in exploring for deposits concealed at depth. For the purpose of this study, restoration of a historical mine data set was undertaken with the goal of migrating information from paper records to fully linked data sets suitable for interpretation in 3-D GIS. Heath Steele, in the Bathurst Mining Camp, northern New Brunswick, is one such deposit with historical records that include the distribution of ore-associated iron formation, massive sulfides and host rocks. Structural and stratigraphic interpretations from previous studies and exploration programs were incorporated in the model, along with fabric measurements, regional geology, drillcore logs and geophysical data. This study shows how revisiting historical mine data in a 3-D environment can generate new knowledge about an ore deposit and particularly the spatial context of hydrothermal features in a complexly deformed setting that may aid future exploration.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".