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Record W2146795711 · doi:10.1190/1.1581031

Repeatability of multimode Rayleigh-wave dispersion studies

2003· article· en· W2146795711 on OpenAlexafffund
K. S. Beaty, Douglas R. Schmitt

Bibliographic record

VenueGeophysics · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsRayleigh waveDispersion (optics)Rayleigh scatteringSurface wavePhase velocityOpticsGeologyRepeatabilityMaterials sciencePhysicsMathematicsStatistics

Abstract

fetched live from OpenAlex

Abstract Rayleigh-wave dispersion is used to study the near-surface elastic properties of a thick, lacustrine clay to approximately 10 m depth. Ten repeated sets of Rayleigh dispersion curves were obtained through late spring to early fall. A variety of methodologies were used to extract the dispersion curves, buta modified frequency-ray parameter (f−p) method most successfully yields dispersion curves for the first three Rayleigh modes. The Rayleigh-wave velocities varied from 100 to ∼350 m/s with frequency over the band from 75 to 10 Hz. Over this band, these velocities did not measurably vary during the study period. The observed phase velocity curves were inverted with P-wave and density values obtained from shallow coring to obtain the shear-wave velocity structure at the site down to >14 m. This case study highlights the robust, repeatable, nature of surface wave dispersion methods when care is taken in the acquisition of field data.

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)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.040
GPT teacher head0.241
Teacher spread0.201 · 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 designObservational
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

Citations92
Published2003
Admission routes2
Has abstractyes

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