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Record W2097846443 · doi:10.1190/1.3223313

Detecting near-surface objects with seismic waveform tomography

2009· article· en· W2097846443 on OpenAlexaffabout
Brendan Smithyman, R. G. Pratt, J. G. Hayles, Ralph Wittebolle

Bibliographic record

VenueGeophysics · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of British ColumbiaGeoscience BCManitoba HydroWestern University
Fundersnot available
KeywordsTomographyWaveformGeologyOffset (computer science)AttenuationSeismologySeismic tomographyGeophysical imagingGeodesyComputer scienceOpticsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

Abstract Three shallow, high-velocity, rubble-filled targets are imaged using waveform tomography in an engineering-scale clay embankment at Seven Sisters Falls, Manitoba, Canada, to locate targets buried at approximately 7 as a blind test of geophysical imaging methods. Previous studies use near-offset reflection methods to image the targets; however, this test uses waveform tomography of the long-offset, refracted arrivals to image P-velocity and seismic attenuation. The targets are invisible to standard traveltime tomography. Using weight-drop data, with frequencies of 20–150 Hz, the subwavelength targets are resolved in the velocity images and complementary images of seismic Q are produced. The interpreted target locations are consistent with limited survey information from the embankment construction. Multiple quality-control efforts, paired with a very good fit between model and observed data, indicate the reliability of the results.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.449

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 head0.006
GPT teacher head0.183
Teacher spread0.177 · 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

Citations40
Published2009
Admission routes2
Has abstractyes

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