Country-scale lithogeochemical interpretation of stream sediment dataset in central Cameroon: Toward an integrated tool to support national geophysics surveys and geological mapping programs
Bibliographic record
Abstract
In the frame of a 1:200,000 mapping project of Cameroon coordinated by PRECASEM for the Ministry of Mine, Industry and Technological Development (MINMITD), between 2016 and 2021, and carried out by BRGM-GTK-BEIG3 Consortium, a dataset of nearly 15,500 stream sediment samples were collected, at an average sampling density of 1 sample per 10 km 2 , over an area of some 157,000 km 2 , and analysed for 49 major and traces elements plus gold. The first aim of the geochemical survey was to identify, at the country scale, metallic anomalies and districts to promote the mining potential of Cameroon to mining investors. In order to expand the use of this unique geochemical dataset, multivariate geostatistical processing by Principal Component Analysis (PCA) and Agglomerative Hierarchical Clustering (AHC) was performed for lithogeochemical purpose. This processing enabled the identification of several lithogeochemical signatures which match very well with the main geological domains and formations obtained by conventional geological field survey. Moreover, in areas covered by thick lateritic profile like in the Adamawa-Yadé subdomain, the geostatistical processing was able to identify the granitic nature of the bedrock. Secondly, the geochemical results obtained for U, K and Th on stream sediments were handled by inverse distance interpolation (IDW), and represented in a ternary combination in the RGB colour space to generate a pseudo-radiometric map to be compared with the high-resolution regional-scale airborne geophysical survey (magnetic and radiometric data) undertaken prior to the beginning of the mapping project. Similarities between both maps are remarkable. Moreover, the pseudo-radiometric map appears also more discriminant in areas covered by thick forest and thick lateritic profile, in humid and swampy environments allowing the identification of structural features and geochemical contrasts unrevealed by the airborne survey. This contribution shows that stream sediment regional-to country-scale dataset should not only be used to highlight the mining potential of the studied area, but also represent a powerful tool, once derived in lithogeochemical and pseudo-radiometric interpretative maps, which can be efficiently used to decipher the major geological contrasts and structural feature of the country rocks. This information is of primary importance to define and calibrate the targets, logistics and costs of the geological field survey classically associated with these national programs, especially in areas with poor outcrops and/or not covered by airborne geophysical surveys. • Country scale stream sediments geochemical prospecting campaign in Cameroon. • Combination of unsupervised analysis to create regional scale lithogeochemical maps. • Main geological domains and boundaries imaged by stream sediments signatures. • Pseudo-radiometric geochemical signal fits with regional airborne geophysical survey.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".