MétaCan
Menu
Back to cohort
Record W1998052414 · doi:10.1109/isspit.2007.4458134

Breath Analysis of Respiratory Flow using Tracheal Sounds

2007· article· en· W1998052414 on OpenAlexaff
Saiful Huq, Azadeh Yadollahi, Zahra Moussavi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicPhonocardiography and Auscultation Techniques
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsRespiratory systemAudiologyMedicineRespiratory soundsSignificant differenceMathematicsAnesthesiaAcousticsInternal medicinePhysicsAsthma

Abstract

fetched live from OpenAlex

While lung sounds intensity is significantly different during inspiratory and expiratory phases, such difference is not audible between the two respiratory phases when listening to tracheal breath sounds. In this study we investigated whether any difference exists between the average power and log-variance of the band-pass filtered tracheal breath sound between the respiratory phases. We used data from 9 healthy subjects without any pulmonary diseases at 4 different flow rates (low, medium, high and very high) and compared the two features at six different frequency ranges from 70 to 1200Hz. The most pronounced differences between the two respiratory phases were found in the 300-450Hz and 800-1000Hz for the average power and log-variance, respectively.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

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

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 head0.040
GPT teacher head0.347
Teacher spread0.307 · 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 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

Citations14
Published2007
Admission routes1
Has abstractyes

Explore more

Same topicPhonocardiography and Auscultation TechniquesFrench-language works237,207