Mineralogical, Geochemical and Distribution Study of Bauxites in the Locality of Bangam and Environs (West Cameroon)
Bibliographic record
Abstract
The bauxite duricrust in the Bangam and surroundings is classified into three major storey levels as follows: the upper level on top of the plateaus where the continuous bauxites outcrop in slabs over distances of about 1 km, the intermediate level on top and at the flanks of the hills where the bauxites flush in metric blocks, the lower level at the talwegs where bauxites duricrust are gravels. The average thickness of the duricrust is 9.6m and extends over an area of about 9.5km2. Five types of facies are encountered here: nodular, pisolitic, pseudobreccia, vacuolar and massive. These different facies were carried out by X-ray fluorescence spectrometry, X-ray diffractometric, thermal analysis (ATD / ATG) and by polarizing microscope observation. The results of these analyses show that, gibbsite is the dominant mineral; kaolinite, anatase, hematite, goethite, magnetite and ilmenite are also present. The chemical composition of the major elements that characterize bauxites are 38-60% Al2O3; 2 -22% SiO2 and 9-42% Fe2O3. These values are almost similar to those obtained in Doumbouo-Fokoué, Ghana, Ngaoundal, and Minim-Martap precisely at Briskok prospect. The different minerals paragenesis and geochemistry data show that, the Bangam locality is a bauxite ore deposit in spite of a high content of iron and silicate of some facies, nevertheless, these can be used in some 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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".