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Record W2115998942 · doi:10.1190/tle33060640.1

Seismic attenuation in partially saturated rocks: Recent advances and future directions

2014· article· en· W2115998942 on OpenAlexaff
Nicola Tisato, Beatriz Quintal, Samuel Chapman, Claudio Madonna, Shankar Subramaniyan, Marcel Frehner, Erik H. Saenger, Giovanni Grasselli

Bibliographic record

VenueThe Leading Edge · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Toronto
FundersLilly Family School of Philanthropy, Indiana University-Purdue University IndianapolisSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsAttenuationBroadbandGeologyFluid dynamicsBandwidth (computing)SeismologyFluid pressureMineralogyAcousticsMechanicsOpticsPhysicsEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Abstract The large amount of data collected with the broadband attenuation vessel (BBAV) and other laboratory devices and analyzed in the last five years sheds light on the physics of wave-induced fluid flow in Berea Sandstone. However, the knowledge is insufficient to fully exploit the physics of seismic wave attenuation in partially saturated rocks. In particular, some technical challenges have limited the depth of research. Soon these challenges will be overcome by the use of fluid-pressure sensors capable of measuring wave-induced fluid pressure in the seismic bandwidth when the sample is under high confining pressures. In addition, a new subresonance apparatus, paired with a micro-CT system, will be used to further investigate the influence of fluid distribution and microstructural features on attenuation.

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)0.006
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations34
Published2014
Admission routes1
Has abstractyes

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