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Record W2316975283 · doi:10.4133/sageep2013-137.1

CROSS-HOLE RADIO IMAGING STUDY, MACLENNAN TOWNSHIP

2013· article· en· W2316975283 on OpenAlexaffabout
Ladan Karimi Sharif, Warren R. Hughes, Xstrata Nickel, Richard D. Smith, Peter K. Fullagar

Bibliographic record

VenueSymposium on the Application of Geophysics to Engineering and Environmental Problems 2013 · 2013
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsLaurentian University
Fundersnot available
KeywordsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

The Nickel Rim South property is located entirely within MacLennan Township, 22 kilometers northeast of Sudbury, Ontario, Canada. The occurrence of conductive sulphides in an otherwise highly resistive host rock makes it an ideal place for exploring and mapping using high frequency electromagnetic methods. The FARA radio imaging (RIM) system was deployed to explore between two proximal boreholes about 100 m apart. Tomographic data were collected at 0.625 and 1.250 MHz. Reciprocal data were also collected, with the transmitter and receiver transferred from one hole to the other. The ImageWin data processing software was used to reduce and edit the data and then to generate attenuation tomograms from the amplitude data. The SIRT algorithm was used for calculating the tomograms. “Weight clamping” was imposed to preserve low attenuation ray paths. Separate tomograms have been created for the original and reciprocal data sets. Finally, the two sets of attenuation coefficients were averaged and imported into Geosoft to create a final tomogram for the panel. There was good qualitative agreement between the ImageWin tomograms and an independent set generated by FARA. However, the FARA tomograms are much smoother. The differences in appearance will be investigated further. Resistivity values were calculated from the attenuation coefficients and are in good agreement with FARA resistivity results. We intend to combine the RIM tomograms with the results from borehole electromagnetic (BHEM) data and physical rock properties derived from wireline borehole logging. Interpreting RIM in conjunction with other data sets will help geophysicists develop a better understanding of the RIM method and its application to geophysical exploration.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.633

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 head0.004
GPT teacher head0.178
Teacher spread0.174 · 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 designSimulation or modeling
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

Citations0
Published2013
Admission routes2
Has abstractyes

Explore more

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