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Record W3021273430 · doi:10.1051/e3sconf/202016800002

Borehole resistivity and induced polarization tomography at the Canadian Shield for Mineral Exploration in north-western Sudbury

2020· article· en· W3021273430 on OpenAlexaboutno aff
Mosaad Ali Hussein Ali, Shulin Sun, Wei Qian, Abdou Dodo Bohari, Claire Dusabemariya, Ajibola Richard Faruwa, Yan Zhang

Bibliographic record

VenueE3S Web of Conferences · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyBoreholeOverburdenMineral explorationMineralization (soil science)Induced polarizationElectrical resistivity tomographyShieldMineralogyEconomic geologyElectrical resistivity and conductivityMining engineeringGeophysicsPetrologySeismologySoil scienceTectonicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Mineral exploration in the Canadian shield is a major challenge nowadays. This is because of the thick overburden cover and complex geology. Borehole tomography using resistivity and induced polarization (BHDCIP) method has a big advantage here due to that the data is acquired underneath the cover and data quality, in general, is superior to that acquired at the surface. BHDCIP provides good resistivity and chargeability data, which can identify mineralization easily. In this study, the BHDCIP survey with high-resolution data was carried out to identify mineralization zones in the McCreedy West zone, north-western Sudbury, Ontario, Canada. Two and three-dimensional (2-D and 3-D) inversion results of three boreholes clearly revealed the mineralization zones and that harmonised with previous geological studies in the study area. The BHDCIP method provided insight and developed an informative subsurface map to identify the mineralization zones, thus proving it as a beneficial tool used for mineral exploration in complex geology with a minimal data survey and an irregular geometrical distribution.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.245
Teacher spread0.197 · 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 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

Citations6
Published2020
Admission routes1
Has abstractyes

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