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Record W4252422754 · doi:10.2310/7070.2005.5016

Contemporary Rhinomanometry

2006· review· en· W4252422754 on OpenAlexaffvenue
P. L. Cole, Ronald S. Fenton

Bibliographic record

VenueThe Journal of Otolaryngology · 2006
Typereview
Languageen
FieldMedicine
TopicNasal Surgery and Airway Studies
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsRhinomanometryMedicineAirflowDecongestantNostrilNosePlethysmographNasal decongestantBreathingAnesthesiaSurgeryMechanical engineering

Abstract

fetched live from OpenAlex

By contrast with the smoked drum and other mechanical systems, modern electronic rhinomanometers provide superior sensitivity and frequency response. They enable accurate measurement of nasal airflow resistance to be made and are commercially available. In addition to a rhinomanometer, nasal airflow measurements require a face mask fitted with a flow measuring device (a pneumotach connected to an electronic differential pressure transducer) or, as an alternative to a face mask, a head-out body plethysmograph. Concurrently with nasal respiratory airflow, transnasal pressures between the nostril and pharynx are measured via nasal or oral tubing by a second differential pressure transducer. The transduced electronic analogue signals are digitized, and nasal airflow resistances are computed from the ratio between transnasal pressure and airflow. At a single sitting, a series of measurements with modern rhinomanometry can determine (1) the response to topical decongestant of the mucovascular contribution to nasal airflow resistance at the time of examination and (2) in the decongested nose, the presence, side, site, and severity of structural obstruction. Rhinomanometry is not "medically necessary" in assessment of all cases of nasal obstructive symptoms, but, in many situations, it can provide valuable objective information in compliance with the requirements of evidence-based medicine. This article includes a table listing situations in which rhinomanometry is particularly useful.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.694
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.081
GPT teacher head0.347
Teacher spread0.266 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations28
Published2006
Admission routes2
Has abstractyes

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