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Record W2586335670 · doi:10.5539/esr.v6n1p142

Estimation of the Depth of Major Subsurface Discontinuities Beneath the Mount Cameroon Region, Central Africa, Based on New and Existing Gravity Data Analysis

2017· article· en· W2586335670 on OpenAlexvenueno aff
Kenfack Jean Vıctor, Joseph Kamguia, Kagou Dongmo Armand, Lucas Kengni, Mbog Michel Bertrand, Bernard Tassongwa, Tabod Tabod Charles

Bibliographic record

VenueEarth Science Research · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsnot available
Fundersnot available
KeywordsClassification of discontinuitiesGeologyBouguer anomalyGravity anomalyCrustSeismologyMountGeodesyGeomorphologyGeophysics

Abstract

fetched live from OpenAlex

The Mount Cameroon region is investigated using 2-D spectral analysis of the gravity data, in order to determine the depth of subsurface interfaces beneath the region. New gravity data are combined to existing ones to determine the depth of the major subsurface discontinuities throughout the region. Depths are established from the slope of the log-power radial spectrum et the lower end of the wave number band. Three major subsurface density discontinuities are determined beneath the Mount Cameroon: (1) 0.41 ± 0.02 km, (2) 1.26 ± 0.06 km, (3) 4.73 ± 0.24 km. This result has the best precision comparing with the those from the former Bouguer anomaly where the major subsurface discontinuities obtained are: (1) 0.48 ± 0.02 km for the first layer, 1.81 ± 0.09 km for the second and 6.87 ± 0.34 km for the third. This difference is probabely due to the densification of gravity data. The knowledge on the depth of different interfaces in the crust is very important in the reconstitution of the earth history. These results will the support of prospective investigations throughout this region.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.475
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.165
GPT teacher head0.378
Teacher spread0.213 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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