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Record W1978273226 · doi:10.1121/1.4781651

Aspects of direct deduction of ground impedance

2007· article· en· W1978273226 on OpenAlexaboutno aff
Keith Attenborough, Shahram Taherzadeh, Gilles A. Daigle, Roland Kruze

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSmoothnessElectrical impedanceAcousticsInstrumentation (computer programming)MinificationMatching (statistics)Computer sciencePoint (geometry)Impedance matchingAlgorithmMathematicsMathematical analysisGeometryPhysicsStatisticsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

ANSI S1.18 1998 offers a method for determining ground impedance by fitting data to templates of the magnitude of level difference obtained using a point source and two vertically separated microphones with specified geometries according the ‘‘acoustical-softness’’ of the ground. The ANSI working group on ground impedance is seeking to revise the current template method for deducing ground impedance by developing a practical method, based in fitting complex level difference spectra and without assuming any particular impedance model. Both minimization and root finding techniques have been used in published laboratory experiments. The results of trial outdoor measurements in the UK, USA, Germany, and Canada are presented. Issues have arisen concerning phase matching of microphones, the signal processing instrumentation, the site and meteorological constraints, and the smoothness of the resulting 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)0.002
metaresearch head score (Gemma)0.018
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.004

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 head0.010
GPT teacher head0.228
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 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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicSeismic Waves and AnalysisFrench-language works237,207