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Record W138010521

Time-Frequency Transform Techniques Applied to Ultra-wideband Ground-Penetrating Radar

2009· article· en· W138010521 on OpenAlexaboutno aff
M. Yedlin, A. Cresp, J. Y. Dauviganc, Stéphane Gaffet, G. Sénéchal, Nicolas Fortino, Christian Pichot, Iannis Aliferis

Bibliographic record

VenueEGU General Assembly Conference Abstracts · 2009
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGround-penetrating radarRadarArt historyHumanitiesPhysicsArtTelecommunicationsEngineering
DOInot available

Abstract

fetched live from OpenAlex

(1) University of British Columbia, Electrical and Computer Engineering, Vancouver, Canada (matt.yedlin@gmail.com/1.604.822.5949), (2) Laboratoire d’E lectronique, Antennes et Te le communications, Universite de Nice Sophia — Antipolis, CNRS, 250, rue Albert Einstein, FR-06560 Valbonne, France, (3) UMR Ge osciences Azur, CNRS/UNSA/IRD/UPMC, Sophia — Antipolis, CNRS, 250, rue Albert Einstein, FR-06560 Valbonne, France , (4) UMR 5212, Mode lisation et Imagerie en Ge osciences, Pau IPRA — Universite de Pau et des Pays de l’Adour, BP 1155, FR-64013 Pau Cedex, France

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)0.000
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.015
GPT teacher head0.256
Teacher spread0.241 · 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
GenreMethods

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

Citations1
Published2009
Admission routes1
Has abstractyes

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