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Record W2977904164 · doi:10.1097/rlu.0000000000002675

Low 68Ga–PSMA PET/CT Uptake in Chronic Intramuscular Nodular Fasciitis

2019· article· en· W2977904164 on OpenAlexaff
Nicolas Plouznikoff, Carlos Artigas, Ioannis Karfis, Patrick Flamen

Bibliographic record

VenueClinical Nuclear Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicUrologic and reproductive health conditions
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineNodular fasciitisProstate cancerFasciitisGlutamate carboxypeptidase IISoft tissueDifferential diagnosisPathologyRadiologyCancerInternal medicine

Abstract

fetched live from OpenAlex

Nodular fasciitis is an uncommon benign mass-forming myofibroblastic proliferation, most frequently found in the upper limbs, with only rare intramuscular cases. We describe herein a case of chronic nodular fasciitis of the left triceps muscle with a low Ga-labeled prostate-specific membrane antigen (PSMA) ligand uptake on PET/CT. Ga-PSMA ligands bind to PSMA-expressing prostate cancer cells, but uptake has also been demonstrated in other solid neoplasms and various benign lesions. Nodular fasciitis should be included in the differential diagnosis of soft tissue lesions with variable Ga-PSMA uptake.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.035
GPT teacher head0.364
Teacher spread0.329 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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