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Record W2142007376 · doi:10.5539/jgg.v4n1p136

Sedimentary Facies Relationships and Depositional Environments of the Maastrichtian Enagi Formation, Northern Bida Basin, Nigeria

2012· article· en· W2142007376 on OpenAlexvenueno aff
Ojo Olusola J., Akande Samuel O.

Bibliographic record

VenueJournal of Geography and Geology · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsnot available
Fundersnot available
KeywordsFaciesGeologySedimentary depositional environmentConglomerateGeochemistryFluvialFloodplainSedimentary rockStructural basinClastic rockGeomorphologySedimentary structures

Abstract

fetched live from OpenAlex

The sedimentary facies of the Maastrichtian Enagi Formation exposed across the Agbona ridge at Share and Shonga areas was investigated for the first time to characterize their depositional facies and interpret the depositional environments. Well exposed vertical profiles of the sediments were studied along road cuts, erosional channels and cliff drops with special attention focused on their internal physical and biogenic attributes. The facies and facies associations in the lithostratigraphic units mapped include conglomerate, sandstone and claystone. The conglomerate facies is moderately sorted; grain supported and mature, showing evidence of reworking and recycling. Association of this facies with herringbone cross stratified sandstone beds probably indicates tidal channel lag origin. The sandstone facies are commonly compositionally mature, bioturbated and contain clasts of reworked clays and clay drapes and these suggest high energy tidal channels and shoreface. The associated unidirectional cross bedded sandstones subfacies and kaolinitic claystones are interpreted as braided fluvial channels and floodplain deposits. The gross sedimentation pattern and characteristics suggest predominance of trangressive shallow marine processes occasionally incised by fluvial channels. The clay deposit associated with the floodplains may offer economic resource potential in the area.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.177
Teacher spread0.167 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations22
Published2012
Admission routes1
Has abstractyes

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