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Record W2153915745 · doi:10.1109/tnsre.2004.841384

Investigating the stationarity of paediatric aspiration signals

2005· article· en· W2153915745 on OpenAlexaff
Tom Chau, D. Chau, Michael J Casas, Glenn Berall, Danelle Kenny

Bibliographic record

VenueIEEE Transactions on Neural Systems and Rehabilitation Engineering · 2005
Typearticle
Languageen
FieldMedicine
TopicRespiratory and Cough-Related Research
Canadian institutionsNorth York General HospitalHospital for Sick ChildrenProfessional Engineers OntarioUniversity of Toronto
Fundersnot available
KeywordsVariance (accounting)SIGNAL (programming language)AccelerationMathematicsMedicineComputer sciencePhysics

Abstract

fetched live from OpenAlex

An aspiration signal is the time-varying anterior-posterior acceleration measured infero-anterior to the thyroid notch when foreign material enters the airway during inspiration. The hypothesis of weak stationarity is tested on aspiration signals by the reverse arrangements test. Results indicate that aspiration signals cannot be uniformly regarded as weakly stationary. Forty-five percent of the examined signals violated the stationarity hypothesis. For these signals, time-varying variance and spectral density structure are identified as major sources of nonstationarity. Stationarity test results generally corroborate qualitative clinical descriptions of aspiration. However, stationarity analysis indicates that aspiration signals are highly heterogenous, a finding which poses significant challenges to the automatic detection of aspirations by accelerometry.

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)0.015
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.263
Teacher spread0.245 · 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

Citations64
Published2005
Admission routes1
Has abstractyes

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