Structural Analysis Using Aeromagnetic Data: Case Study of Parts of Southern Bida Basin, Nigeria and the Surrounding Basement Rocks
Bibliographic record
Abstract
Structural analysis using aeromagnetic data over parts of southern Bida (Nupe) basin, Nigeria and the surrounding basement rocks was carried out to highlight linear structures and infer the effects of such features on the tectonic events in the survey area. The basin consists of the basal Lokoja Formation, overlain by the Patti Formation and capped by the Agbaja Formation. The basal Lokoja Formation is a sequence of matrix supported conglomerates and sandstones overlying the Pre–Cambrian to lower Palaeozoic basement. Magnetic rocks (iron ore) occur at the central, north eastern and south southern sections of the study area. Trend characteristics of magnetic lineaments were highlighted using the Euler deconvolution method. Werner and Euler deconvolution of aeromagnetic data profiles were utilized to determine the depth to magnetic sources. Depth to magnetic sources along aeromagnetic data profiles ranges from 0.01 km to 0.51 km with an average value of 0.128 km. Deductions made from the research are; mineralization is structurally controlled in parts of the survey area with kaolin occurring along a lineament around Share, western part of the survey area. The occurrence of subsurface linear structures may be due to discontinuities caused by faulting of country rock. Lineaments’ trends inferred include the east–west, north–south, northeast–southwest, north northeast–south southwest and northwest–southeast directions, with the north northeast–south southwest trend being dominant. Werner deconvolution plots for profiles ZZ and HH located at the central and southern sections of the survey area respectively; are inferred to be basement rock fractures beneath the sedimentary rock.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".