Applicability of standard Euler deconvolution, modeling and amplitude magnetic data inversion in Greenfield programs: The Leite target case study - Carajas Mineral Province - Brazil
Bibliographic record
Abstract
The Leite target is located in Carajas Mineral Province and has a magnetic anomaly with 140 nT of amplitude, elongated in the northwest-southeast direction. Four exploratory drillholes were performed to test the magnetic anomaly. The test showed that the source of the anomaly is a narrow magnetite hydrothermal alteration zone bearing copper mineralization up to 2%. In addition, geologic and geochemical data, magnetic susceptibility (MS) measurements were collected to identify the lithotypes with ferromagnetic minerals. We use three different techniques to estimate the depth and geometry of the magnetic source: standard Euler deconvolution, total field magnetic anomaly modeling, and magnetic amplitude inversion. When visualized in 3D, the depth of solutions from Euler deconvolution crossed the real magnetic layer with less inclination. The modeling, using the solutions from Euler deconvolution, was performed, and the magnetic anomaly produced by the body modelled achieved a low misfit. The body used in the forward modeling is geometrically similar to the geologic magnetic layer. The magnetic amplitude inversion successfully recovered the MS distribution. Finally, we carried out a borehole magnetic survey in two drillholes to validate the obtained models and investigate the magnetic source. This survey confirmed that the models were intercepted and the magnetic anomaly was associated, a hydrothermal alteration zone, with magnetite intercepted by drillholes. In this study, we demonstrated that the use of those techniques was effective in Greenfield exploration programs
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".