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Record W1576732803 · doi:10.1109/iembs.2004.1403173

A novel method of estimation of DPOAE signals

2005· article· en· W1576732803 on OpenAlexaff
A.K. Ziarani, A. Konrad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicECG Monitoring and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceSIGNAL (programming language)Noise (video)SoftwareMeasure (data warehouse)Nonlinear systemNoise immunityAlgorithmSimplicityArtificial intelligenceData miningTransmission (telecommunications)Image (mathematics)

Abstract

fetched live from OpenAlex

A new method of measurement of DPOAE signal level based on a recently introduced nonlinear adaptive method of extraction of nonstationary sinusoids is presented. Essentially, three units of such an algorithm are employed to extract and measure the two stimuli and the DPOAE signal. Each unit has the capability of locking on a specified sinusoidal component of the input signal and tracking its variations over time. Performance of the proposed method is demonstrated with the aid of computer simulation and is verified in laboratory using recorded clinical data. Comparison is made between the proposed technique and existing methods. The proposed method features structural simplicity which renders it particularly attractive for implementation on both software and hardware platforms. It offers a high degree of immunity with regard to background noise and parameter variations. Compared to conventional methods, the proposed method offers a shorter measurement time which is of significant value in clinical examinations.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.467
Threshold uncertainty score0.165

Codex and Gemma teacher scores by category

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

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 head0.037
GPT teacher head0.379
Teacher spread0.342 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2005
Admission routes1
Has abstractyes

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