MétaCan
Menu
Back to cohort

Nodular fasciitis of the head and neck region: a clinicopathologic description in a series of 30 cases

2009· article· en· W1967380562 on OpenAlexaff
Ilan Weinreb, Allison J. Shaw, Bayardo Perez‐Ordoñez, John R. Goldblum, Brian P. Rubin

Bibliographic record

VenueJournal of Cutaneous Pathology · 2009
Typearticle
Languageen
FieldMedicine
TopicSoft tissue tumor case studies
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsNodular fasciitisMedicineTrunkPathologyDifferential diagnosisMyofibroblastHead and neckSoft tissueFasciitisLesionRadiologySurgeryBiologyFibrosis

Abstract

fetched live from OpenAlex

Nodular fasciitis (NF) is a reactive lesion composed of fibroblasts/myofibroblasts and most commonly found in extremities and trunk. NF has been described in the head and neck region (HNR) in 13-20% of cases. It is our impression based on consultation experience that many pathologists do not consider NF in the differential diagnosis of soft tissue masses arising in the HNR. Moreover, it is common for these lesions to be incompletely excised, leading to additional challenges in diagnosis. We describe 30 cases of NF of the HNR in order to focus attention on this frequently overlooked diagnosis. While they had the typical histologic features of NF, the lesions had a tendency for smaller size, increased skeletal muscle involvement (30%) compared to fasciitis elsewhere in the body and diffuse and strong actin expression. Follow up demonstrated one recurrence (7.1%) higher than reported elsewhere in the body. These latter features may add to the challenge in diagnosing NF in these locations.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.298
Teacher spread0.258 · 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 designCase report
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

Citations58
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cutaneous PathologySame topicSoft tissue tumor case studiesFrench-language works237,207