Field Observations and Geophysical Research Applied to the Detection of Manganese (Mn) Deposits in the Eastern Part of Oban Massif, South-Eastern Nigeria: An Integrated Approach
Bibliographic record
Abstract
The growing need for an industrialized world, especially in Africa, cannot be feasible without adequate mineral resources. Thus, the search for more mineral deposits will continue to be necessary. An integrated approach involving geological mapping and a high-resolution geophysical (aeromagnetic) investigation was conducted to assess the manganese mineralization in parts of the Oban Massif, southeast Nigeria. The aeromagnetic data were processed using regional-residual anomaly separation techniques, first vertical derivative (1VD), analytical signals, source parameters imaging (SPI), and Euler deconvolution to better understand magnetic source distributions and their depths of occurrence. The geological investigation revealed a dominant variety of metamorphic rock types, including migmatitic (banded) gneisses hornblende granite gneisses, amphibolites, charnockites, and some quartzite ridges. Also present are some indications of pockets of dolerites. The study area also observed epithermal Mn+Fe+Qtz vein type mineralization associated with hydrothermal alteration zones whose orientation coincides with dominant structural orientation from aeromagnetic interpretation. Analysis of aeromagnetic data shows that the study area is dominated by ENE, NNE, and E-W structural directions (near-surface basement structures), with the ENE trends related to mineralization in the area. The manganese mineralization within Oban Massif is structurally controlled. The depths of the magnetic anomalies in the study area were estimated using SPI and Euler decomposition algorithms. SPI delineated the shallow, intermediate, and deep magnetic anomalies at 84–142 m, 152–200 m, and 215–656 m, respectively. Euler decomposition, however, revealed that shallow, intermediate, and deep depths occurrence of the magnetic anomalies are at 200–377 m, 393–472 m, and 499–793 m, respectively.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".