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Record W2533303383 · doi:10.1109/iembs.1991.684045

Use Of Autocorrelation To Improve The Three Dimensional Plot Of Transcutaneous Human electrogastrograms

2005· article· en· W2533303383 on OpenAlexaff
Martin P. Mintchev, Y.J. Kingma, K.L. Bowes

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAutocorrelationPlot (graphics)AmplitudeInterpretation (philosophy)Computer sciencePower (physics)Spectral densityFrequency bandSpike (software development)Speech recognitionAcousticsArtificial intelligenceMathematicsStatisticsTelecommunicationsPhysicsBandwidth (computing)Optics

Abstract

fetched live from OpenAlex

Transcutaneous human electrogastrograms (EGG) have been recorded for many years without significant improvement in their interpretation. The application of amplitude or power spectrum analysis is a powerful method to analyse EGG signals which have a relatively narrow frequency band and infralow fundamental frequencies (0.03-0.1 Hz) . Three dimensional plots are often used to represent the dynamics of the amplitude or power changes in the EGG signals vs. frequency and time. Because of the movement and respiratory artifacts three dimensional plots are not always clear enough to allow further interpretation of the results. In this paper we address that problem suggesting three dimensional plot of the autocorrelated EGG signals. The proposed method minimizes the influence of the artifacts and provides both repeatable results and good possibilities for interpretation.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.222
Teacher spread0.205 · 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 designSimulation or modeling
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

Citations1
Published2005
Admission routes1
Has abstractyes

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