Analysis of the Spatial Distribution of Geology and Pedologic Formations in Gombe State, North Eastern Nigeria
Bibliographic record
Abstract
This paper focused on the mapping and analysis of the spatial distribution of the geology and soils in Gombe State. The ever rapid rise in population of the country has called for the need for expansion of agricultural activities which necessitates an in-depth knowledge of the spatial location of soil types for agricultural related activities. There is also the need to explore the environment for possible endowments of mineral resources which can be exploited to meet the economic demands of the populace. The soil and geology maps of Gombe State were extracted from existing soil and geology maps of Nigeria, obtained from Food and Agricultural Organization (FAO)/United Nations Education, Scientific and Cultural Organization (UNESCO)/International Soil Reference and Information Center (ISRIC) and Nigeria Geological Survey Agency (NGSA) respectively. The soil and geology types were digitized as polygon, while other important features such as LGA boundaries, state boundaries were also digitized and overlain on the two generated maps (soils and geology). The clip sub module of the ArcGIS was used to delineate each of the LGAs in both maps, that is, extraction of each LGA as well as the soil and geology units in each of the LGAs. The area in square kilometers of the soils and geology units in the entire state and in each LGA were obtained through the use of the area calculation module of the ArcGIS. The result of the study revealed that Gombe State consists of fourteen (14) geologic units. Among them, the KerriKerri which comprised of sandstone, shale and clay geologic unit covers almost half (42.75%) of the State. Limestone and Shale of the Pindiga formation which are principally used for cement making are found mainly in Funakaye LGA which is the home of Ashaka Cement. It was also found out that there are eleven soil units in the state with Nitisols almost covering half of the state. It was recommended that the generated soil and geologic maps of the State are expected to be considered for mineral exploration and crop suitability assessments in order to reduce time, cost and energy that would likely be incurred if the entire state is assessed.
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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 | 0.000 | 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 | 0.001 |
| 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".