Compositional, Geotechnical and Industrial Characteristics of Some Clay Bodies in Southern Nigeria
Bibliographic record
Abstract
Clay occurrences at Okija, Ubiaja and Iyuku in southern Nigeria were characterized geochemically, mineralogically as well as geotechnically in order to evaluate their industrial potentials. Mineralogical analyses portray kaolinite as the dominant clay mineral with traces of illite in the transported Okija and Ubiaja samples. Abundances of major elements show that SiO2 (ca 50.41-64.45%) and Al2O3 (ca 18.62-31.62%) constitute over 80% of the bulk chemical compositions. Other constituents include Fe2O3, K2O, TiO2, CaO, MgO and MnO. Although notable disparities exist in the SiO2 and Al2O3 contents of the clays, the Iyuku sample is more siliceous and less aluminous than the others. Geotechnically, the in-situ derived Iyuku clay has distinctive characteristics. It is considerably less plastic, non-expansive, less hydrophilic and of low compressibility due to its lower clay fraction and higher crystallinity of available kaolinites. On the other hand, the Okija and Ubiaja clays are characterized by medium to high plasticity and compressibility. The shrinkage characteristics of the clays as well as their colloidal activities are consistent with their plasticity. Evaluation of the industrial potential of the clays based on their physical, chemical and geotechnical characteristics revealed that they are suitable for the production of refractory bricks and ceramics. Appropriate processing/beneficiation would be mandatory if they are to qualify for other industrial applications, such as rubber, paper, paint and cosmetic industries.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".