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Simulated annealing inversion of multimode Rayleigh wave dispersion curves for geological structure

2002· article· en· W2109717268 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeophysical Journal International · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInversion (geology)Superposition principleSimulated annealingRayleigh waveGeologySurface waveOpticsMathematical analysisMathematicsAlgorithmPhysicsSeismology

Abstract

fetched live from OpenAlex

A R Y Simulated annealing was used to invert fundamental and higher-mode Rayleigh wave dispersion curves simultaneously for an S-wave velocity profile. The inversion was applied to near-surface seismic data (with a maximum depth of investigation of around 10 m) obtained over a thick lacustrine clay sequence. The geology was described either in terms of discrete layers or by a superposition of Chebyshev polynomials in the inversion and the contrasting results compared. Simulated annealing allows for considerable flexibility in model definition and parametrization and seeks a global rather than a local minimum in a misfit function. It has the added advantage in that it can be used to determine uncertainties in inversion parameters, thereby highlighting features in an inverted profile that should be interpreted with caution. Results show that simulated annealing works well for the inversion of multimodal near-surface Rayleigh wave dispersion curves relative to the same inversion that employs only the fundamental mode.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.338
Threshold uncertainty score0.996

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)0.0050.000

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 head0.026
GPT teacher head0.229
Teacher spread0.203 · 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