Integration of Electrical Resistivity Tomography and Induced Polarization for Characterization and Mapping of (Pb-Zn-Ag) Sulfide Deposits
Bibliographic record
Abstract
The accurate characterization and mapping of low-grade ore deposits necessitate the utilization of a robust exploration technique. Induced polarization (IP) tomography is a powerful geophysical method for mineral exploration. An integrated survey using electrical resistivity tomography (ERT) and IP was employed in this study to characterize and map (Zn-Pb-Ag) ore deposits in NE New Brunswick, Canada. The survey encompassed twelve parallel lines across the study area. The 2D and 3D inversion of the results provided a detailed image of the resistivity and chargeability ranges of subsurface formations. The boundaries of sulfide mineralization were determined based on resistivity values of (700–2000 Ohm.m) and chargeability values of (3.5 mV/V) and were found to be located at an approximate depth of 80–150 m from the surface. The findings were validated through a comparison with data from borehole logs and mineralogy data analysis. The size and shape of sulfide deposits were successfully characterized and mapped in the study area using this cost-effective mapping approach.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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)
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".