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Record W4376651109 · doi:10.14639/0392-100x-n2118

Spatial analysis of transnasal olfactory cleft access: a computed tomography study

2023· article· en· W4376651109 on OpenAlexaff
Teffran J. Chan, Melissa Lee, Andrew Thamboo

Bibliographic record

VenueActa Otorhinolaryngologica Italica · 2023
Typearticle
Languageen
FieldMedicine
TopicNasal Surgery and Airway Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCribriform plateMedicineCribriformNoseIntraclass correlationEthmoid boneNasal septumRadiographyAnatomyNasal cavityOrthodonticsSurgeryPathology

Abstract

fetched live from OpenAlex

Objective: To our knowledge, the spatial access of naris to olfactory cleft has not been quantified. We aimed to study the relationship and space of middle turbinate, septum, anterior nasal spine and cribriform plate to improve topical medication delivery and drug applicators. Methods: One hundred CT scans of patients (50 males, 50 females) over the age of 18 were included. Subjects with radiographic sinonasal pathology, previous surgery, or specific variant nasal anatomy were excluded. Scans were independently reviewed and bilateral measurements on bony landmarks were taken by two blinded authors. Inter-rater reliability was analysed with intraclass correlation. Results: The average age was 46.26 years (σ = 14.0). Average distance from the anterior nasal spine to olfactory cleft was 52.3 mm (σ = 4.2 mm), and the average length of cribriform plate was 18.8 mm (σ = 3.8) with an angle relative to hard palate averaging -8.8 degrees below parallel (σ = 5.5 degree). The widths of the olfactory cleft at anterior and posterior edges of cribriform plate were 2.3 mm (σ = 0.7 mm) and 2.0 mm (σ = 0.7 mm). Conclusions: The findings suggest a 52.3 mm distance from the naris to the anterior border of cribriform plate. The average width along this path was 3.2 mm, suggesting devices narrower than this could potentiate direct drug delivery access.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.005
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 head0.056
GPT teacher head0.308
Teacher spread0.251 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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