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Record W2328585905 · doi:10.1190/1.3255520

Multifrequency singular spectrum analysis

2009· article· en· W2328585905 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

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicStatistical and numerical algorithms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSingular spectrum analysisSpectrum (functional analysis)GeologySpectral analysisComputer sciencePhysicsAlgorithmSingular value decompositionSpectroscopyAstronomy

Abstract

fetched live from OpenAlex

Singular spectrum analysis (SSA) is a method utilized for the analysis of time series arising from dynamical systems. The method is used to capture oscillations from a given time series via the analysis of the eigen‐spectra of the Hankel matrix of the data. The Hankel matrix is composed of multiple data views. The singular value decomposition (SVD) of the Hankel matrix can be used for rank reduction and noise elimination. We apply SSA in the f ‐ x domain and present a comparison with classical f ‐ x deconvolution. In addition, we propose a multifrequency version of Singular Spectrum Analysis (MF‐SSA) where a band of adjacent frequencies is utilized to construct the block Hankel matrix of the problem.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.579
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.327
Teacher spread0.294 · 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

Quick stats

Citations26
Published2009
Admission routes1
Has abstractyes

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