Analysis of petrophysical properties of rocks from the Bathurst Mining Camp: Constraints on gravity and magnetic modeling
Bibliographic record
Abstract
Abstract Understanding the physical rock properties of different lithologies within a mining district allows one to link geologic observations with geophysical interpretations. This paper presents a physical rock property database for the Bathurst Mining Camp (BMC). Density–magnetic susceptibility bivariate plots are used to illustrate patterns indicative of changes in the concentration of paramagnetic versus ferrimagnetic mineral phases. Q-Q plots and histograms are used to determine if a lithology is characterized by a unimodal or multimodal physical property population. To use the physical property data in geophysical models, the rock classification was reduced to five lithological groups and three subgroups. The results of two geophysical modeling exercises, using lithological and petrophysical data as input constraints, are presented. Late-stage deformation of the BMC resulted in two large-scale plunging folds: the Nine Mile Synform (NMS) and the Tetagouche Antiform. The subsurface geometry of the NMS along the model profile was initially estimated from surficial geology maps projected down the plunge of the fold axis. Geophysical data requires dense and magnetic volcanics on the east limb of the Nine Mile Syncline to be nearer to the surface than previously expected. The magnetic anomaly associated with the Armstrong B mineral deposit was modeled using constrained discrete object source geometry. To achieve a satisfactory match between the observed and calculated data requires a significant component of magnetic remanence. The orientation of the calculated remanence vector is similar to a paleomagnetically determined in situ direction and to the direction estimated for Laurentia during the Paleozoic. The source body estimated by the inversion is significantly larger than the known thickness of the ore zone. This is a consequence of computing the inversion on a gridded aeromagnetic data set, which has a cell size that is larger than the known thickness of the ore body.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".