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Record W2588653861 · doi:10.3130/aijs.71.55_2

IDENTIFICATION OF DAMPING FACTOR CONSIDERING ITS LOWER LIMIT BY SPECTRAL RATIO INVERSION : Application to borehole array records at hard rock sites and evaluation of attenuation characteristics

2006· article· en· W2588653861 on OpenAlexaff
H. Sato, Mamoru Kanatani, Yasuki Ohtori

Bibliographic record

VenueJournal of Structural and Construction Engineering (Transactions of AIJ) · 2006
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsBoreholeAttenuationDamping ratioInversion (geology)Limit (mathematics)GeologyInverse transform samplingGeotechnical engineeringAcousticsSeismologyPhysicsOpticsMathematicsVibrationMathematical analysis

Abstract

fetched live from OpenAlex

A spectral inversion method adopting new functional model of damping factor with its lower limit is proposed for identifying more sophisticated attenuation characteristics of rock sites. The proposed model is applied to borehole array data recorded at hard rock sites. The identified lower limits of damping factor agree well with experimental material damping factors derived from laboratory test of rock samples. Therefore it can be interpreted that the lower limit of proposed model may be corresponding to actual material damping factor. Moreover, we indicate that frequency dependent characteristics of the damping factor at rock sites could be interpreted as a theoretical damping due to scattering of inhomegeneous rock.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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