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Record W2330437909 · doi:10.1071/aseg2009ab077

Airborne geophysics as a tool to promote mineral investment in africa

2009· article· en· W2330437909 on OpenAlexaff
Stephen Reford, Karl Kwan, J. Nyakaana, Andrew Katumwehe, O. Wane

Bibliographic record

VenueASEG Extended Abstracts · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsGeoscience BCWorld Wildlife Fund Canada
Fundersnot available
KeywordsMineral explorationMineral resource classificationGeologyInvestment (military)Resource (disambiguation)Sustainable developmentEarth scienceGeographyGeophysicsPolitical scienceGeochemistry

Abstract

fetched live from OpenAlex

Airborne geophysics, particularly aeromagnetic and gamma-ray spectrometer (radiometric) surveys, forms a critical component of geological mapping and mineral resource inventory programs in many African countries. In the 60?s and 70?s, regional aeromagnetic surveys were fairly widespread over much of the continent, in both sedimentary and hard rock terrains (Barritt, 1993). In the 80?s and 90?s, higher resolution surveys, incorporating radiometrics, were carried out in certain countries, particularly in southern Africa. In the last decade, a number of national initiatives (e.g. Madagascar, Mozambique, Namibia, Morocco, Mauritania, Nigeria, Ghana, etc.) have seen the high-resolution geophysical coverage greatly improve. The surveys form part of larger initiatives to improve the geological knowledge of a country or region, with the ultimate objective of increasing mineral investment and developing a sustainable mining industry. These geoscience programs are typically accompanied by reforms in the mining law to promote such investment. They contribute to tectonic reconstruction, groundwater and environmental applications, and petroleum exploration, all of which ultimately assist societal development (Reeves, 2005). International funding agencies such as the World Bank, European Community and African Development Bank have seen the value in such programs, and ensure that airborne geophysics receive a large share of project budgets. In jurisdictions throughout the world, it has been demonstrated that high-quality geophysical coverage leads directly to increased and more focused exploration. A trend in the last few years has been the inclusion of an airborne electromagnetic follow-up component to the airborne program. This paper provides current examples from two countries. In Uganda, more than 600,000 line-km of magnetic and radiometric data are being acquired over most of the country. In addition, eight blocks with high mineral potential are being flown with electromagnetic systems (Tempest and heliGeotem). In Senegal, the entire hard rock region has been covered by 130,000 line-km of magnetic and radiometric data, followed by a Tempest survey over three large blocks.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations4
Published2009
Admission routes1
Has abstractyes

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