Interpretation of aeromagnetic data for estimation of Curie point depth in Sokoto Basin, Nigeria
Bibliographic record
Abstract
This research studied the estimation of the Curie point depth isotherm using aeromagnetic data across Sokoto Basin, Northwest, Nigeria. The study area lies within the longitudes of 3–7° east and latitudes of 10–14° north. The residual–regional separation was carried out on the total magnetic intensity using polynomial fitting of the second order. The residual map that formed the basis for analysis and interpretation was divided into 30 spectral blocks. Hence, the log of the spectral energies was plotted against the frequency using a spectral program plot developed with Matlab. The obtained results of centroid depth and depth to the top boundary were used in estimating the Curie point depth isotherm, which serves as the depth at which the crust and uppermost mantle magnetic materials cease to be magnetic. Interestingly, the results obtained from the spectral analysis of the study area, where an average depth to the top boundary of 2.2 6 km was obtained, indicated a good spot for hydrocarbon potential. The Curie point depth within the study area varied between 5.96 and 74.29 km with an average depth of 18.99 km. Impliedly, the results obtained from the Curie point depth isotherm indicated a good source of geothermal potential in the study area.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".