MétaCan
Menu
← Back to cohort
Record W2326267483 · doi:10.1190/1.3255399

Seismic anisotropy measurements and theoretical model of fractured rock using multi‐depth multi‐azimuth walk‐away VSP from Outokumpu, Finland

2009· article· en· W2326267483 on OpenAlexafffund
Heather Schijns, Douglas R. Schmitt, Pekka Heikkinen, Ilmo Kukkonen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeologyAnisotropyBoreholeAzimuthSchistLithologyVertical seismic profileSeismologySeismic surveySeismic anisotropyMineralogyPetrologyGeophysicsGeotechnical engineeringGeometryMetamorphic rockOptics

Abstract

fetched live from OpenAlex

A high resolution multi-azimuth multi-depth walk-away VSP is used to measure velocity anisotropy in the Outokumpu area of the Fennoscandian shield. The 2.5 km deep borehole used for the survey shows the area lithology to be primarily mica-rich schist, and the area is expected to demonstrate anisotropy as a result of lattice-preferred orientation of biotite and of aligned fractures. Through the application of a ι -p transform to the walk-away VSP data set, qP- and qS-wave phase velocities are calculated. A three dimensional velocity model is developed using the phase velocity measurements from the shallowest walkaway VSP where the receiver was at a depth of 1000 m. These velocities are modeled under the assumption that the schist can be represented as a fractured orthorhombic media. A good fit is achieved between the model and experimental results, and the accuracy of the theoretical model is further investigated through comparison with known geology.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.052
GPT teacher head0.261
Teacher spread0.209 · 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 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
Published2009
Admission routes2
Has abstractyes

Explore more

Same topicSeismic Imaging and Inversion Techniques→French-language works237,207→