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Country-scale lithogeochemical interpretation of stream sediment dataset in central Cameroon: Toward an integrated tool to support national geophysics surveys and geological mapping programs

2025· article· en· W4407856788 on OpenAlexaff
Guillaume Vic, J. Bernard, M. Chevillard, Laurent Bailly, Constantin Maurice Ndongue, Y. Itard, Jérémie Melleton, Guillaume Martelet, Etienne Kouokam, Eric Fournier, Renaud Couëffé, D. Keutia

Bibliographic record

VenueApplied Geochemistry · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsNutrasource
Fundersnot available
KeywordsGeologic mapScale (ratio)Interpretation (philosophy)GeologySedimentEarth scienceCartographyGeomorphologyGeographyComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.248
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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