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Controlled sources for shear‐wave surveys in mines

2000· article· en· W2019158222 on OpenAlexafffund
Gordon M. Holmes, Stuart Crampin, R. P. Young

Bibliographic record

VenueGeophysical Prospecting · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsGeological Survey of Canada
FundersKeele UniversityCANDU Owners Group
KeywordsShear (geology)Shear wave splittingGeologySeismologyShear wavesAnisotropyGeotechnical engineeringOpticsPetrologyPhysics

Abstract

fetched live from OpenAlex

The ability to analyse shear‐wave anisotropy in a mine environment is greatly aided by using multiple source orientations of a reproducible, impulsive shear‐wave source. The analysis of what is probably the first controlled source shear‐wave experiment in a mine environment demonstrates clearly that shear‐wave polarizations and time delays between split shear‐wave arrivals are reliably measured because of the use of multiple source orientations rather than a single shear‐wave source. Reliability is further aided by modelling the shear‐wave source radiation pattern, which allows for the unequivocal discrimination between seismic raypaths where shear‐wave splitting did and did not occur. The analysis also demonstrates the great importance of high reproducibility of the seismic source for the use of shear waves in time‐lapse surveys to monitor changes in a rockmass.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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 designOther design
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

Citations2
Published2000
Admission routes2
Has abstractyes

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