MétaCan
Menu
Back to cohort
Record W4404412349 · doi:10.3138/cjms-2024-0007

Three Sonographic Findings to Look for in Fibromatosis Colli: Scanning Tips and Report of Two Cases

2024· article· en· W4404412349 on OpenAlexaff
Karen Letourneau, Amandeep Dusanj, Lindsay Deeble

Bibliographic record

Venue˜The œCanadian journal of medical sonography. · 2024
Typearticle
Languageen
FieldMedicine
TopicSoft tissue tumor case studies
Canadian institutionsIsland Health
Fundersnot available
KeywordsFibromatosisMedicineRadiology

Abstract

fetched live from OpenAlex

Fibromatosis colli is a rare, benign mass of the sternocleidomastoid muscle (SCM), typically diagnosed in infants between weeks 1 to 8 of life. Physical examination of the infant will exhibit a firm lump on the affected side of the neck. The mass is typically unilateral and may be accompanied by torticollis. We present two cases of infants with fibromatosis colli. Sonographic examination is the preferred initial non-invasive diagnostic procedure, with 100% sensitivity. Ultrasound can confirm the diagnosis, avoiding unnecessary invasive interventions. Early diagnosis can prevent complications such as plagiocephaly, facial asymmetry, and scoliosis. We aim to provide the tools necessary to recognize fibromatosis colli by describing three key sonographic appearances. We will present two separate cases that demonstrate these findings and discuss how to sonographically rule out the many differential diagnoses.

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)0.001
metaresearch head score (Gemma)0.008
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.002
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.031
GPT teacher head0.316
Teacher spread0.285 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venue˜The œCanadian journal of medical sonography.Same topicSoft tissue tumor case studiesFrench-language works237,207