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Record W2317292009 · doi:10.1097/rct.0000000000000196

Computed Tomography Appearance of Normal Nonossified Thyroid Cartilage

2015· article· en· W2317292009 on OpenAlexaff
Nazanin Dadfar, Mohammad Seyyedi, Reza Forghani, Hugh D. Curtin

Bibliographic record

VenueJournal of Computer Assisted Tomography · 2015
Typearticle
Languageen
FieldMedicine
TopicOropharyngeal Anatomy and Pathologies
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineComputed tomographyTomographyThyroidThyroid cartilageCartilageRadiologyNuclear medicineAnatomyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to determine the density and homogeneity of the nonossified thyroid cartilage (NOTC) on contrast-enhanced computed tomography (CT) providing preliminary information for future evaluation of cartilage invasion using dual-energy CT. METHODS: One hundred normal-larynx CT scans were evaluated for the density and homogeneity of NOTC. RESULTS: The density of the NOTC was homogeneous in all cases. Nonossified thyroid cartilage had higher mean density than contiguous muscle, but there was overlap. In 47 cases, a lucent area was observed at the junction of the ossified and NOTC but not within the NOTC itself. In 11 cases, ossification was observed in only 1 cortex of the thyroid cartilage. Cartilage at the anterior commissure was not ossified in 7 cases. CONCLUSIONS: Nonossified thyroid cartilage has a homogeneous appearance on contrast-enhanced CT scans, but showed some normal variations that could be mistakenly reported as tumor invasion.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.262
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2015
Admission routes1
Has abstractyes

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