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Record W2028725734 · doi:10.2500/ajr.2007.21.3039

Reproducibility of Acoustic Rhinometry in the Investigation of Occupational Rhinitis

2007· article· en· W2028725734 on OpenAlexaff
Roberto Castaño, Gilles Thériault, Denyse Gautrin, Heberto Ghezzo, Carole Trudeau, Jean‐Luc Malo

Bibliographic record

VenueAmerican Journal of Rhinology · 2007
Typearticle
Languageen
FieldMedicine
TopicNasal Surgery and Airway Studies
Canadian institutionsHôpital du Sacré-Cœur de MontréalMcGill University
Fundersnot available
KeywordsAcoustic rhinometryReproducibilityMedicineIntraclass correlationRhinomanometryNoseNuclear medicineDentistrySurgeryMathematicsStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: To diagnose occupational rhinitis, it is mandatory to conduct an objective assessment of changes in nasal patency during specific inhalation challenge (SIC). The reproducibility of acoustic rhinometry measurements in the setting of occupational challenges has never been examined. This study assessed the reproducibility of acoustic rhinometry during SIC investigation of occupational rhinitis. METHODS: Twenty-four subjects underwent acoustic rhinometry measurements during SIC investigation of occupational rhinitis. Subjects attended 3-6 days of SIC within a week by means of a realistic or closed-circuit apparatus methodology RESULTS: All of the within-day intraclass correlation coefficients (ICCs) for nasal volume (2-5 cm) and minimum cross-sectional area (MCA) based on a different number of measurements (2-7) were above 0.85; all of the coefficients of variation (CVs)for the same parameters were low (below 10%). The between-day CVs based on different numbers of SIC sessions ranged from 8.0 to 8.8% and from 6.8 to 8.8%for nasal volume and MCA, respectively. The between-day ICCs ranged from 0.80 to 0.88 and from 0.83 to 0.94 for nasal volume and MCA, respectively. CONCLUSION: Acoustic rhinometry showed good within- and between-day reproducibility and can be recommended for the objective monitoring of nasal patency during SIC investigating occupational rhinitis.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.021
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.043
GPT teacher head0.329
Teacher spread0.286 · 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

Citations19
Published2007
Admission routes1
Has abstractyes

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