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Record W4289931295 · doi:10.1016/j.sesci.2022.07.001

Trace elements geochemistry, total organic carbon, palaeosalinity, and hydrothermal characteristics of the Cretaceous black shale in the Mamfe Basin (West Africa)

2022· article· en· W4289931295 on OpenAlexafffund
Bokanda Ekoko Eric, Philip Fralick, Bisse Salomon Betrant, Ashukem Ethel Nkongho, Belinga Belinga Cédric, Bokanda Frankline Besonge, Ligbwah Victor Wotanie, Chin Thiery Berinyuy, Ekomane Emile

Bibliographic record

VenueSolid Earth Sciences · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaLakehead University
KeywordsHydrothermal circulationTotal organic carbonGeologyOil shaleGeochemistryMineralogyDeposition (geology)Environmental chemistryStructural basinChemistryPaleontology

Abstract

fetched live from OpenAlex

The shales of the Mamfe basin were geochemically analyzed to determine their paleosalinity and hydrothermal characteristics which existed at the time of their deposition. Elemental ratios such as boron/gallium (B/Ga), strontium/barium (Sr/Ba), and total sulphur/total organic carbon (S/TOC) and TOC/S were applied for paleosalinity reconstruction. The shales of the Mamfe basin show B/Ga is <3, Sr/Ba <0.2, and S/TOC is <0.1 and TOC/S >6 the values of the elemental ratio show that the Mamfe shales were deposited in a freshwater environment. For hydrothermal activities ratio, Sc/Cr was used and Binary diagrams TOC vs P and Co/Zn vs TOC were constructed to discriminate between normal water, mixed and hydrothermal influence. The Sc/Cr ratio was greater than 0.14 indicating that the shales in the Mamfe basin were deposited in a normal water environment with no influence from hydrothermal processes. The binary discriminant diagram of TOC vs P and Co/Zn vs TOC shows that all the shales were not influenced by any hydrothermal processes during the time of their deposition.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.997

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.208
Teacher spread0.195 · 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 designObservational
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

Citations13
Published2022
Admission routes2
Has abstractyes

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