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Record W2500847302 · doi:10.1155/2016/2526789

Needle Fracture during Endoscopic Ultrasound-Guided Fine-Needle Aspiration of Suspicious Thoracic Lymph Nodes

2016· article· en· W2500847302 on OpenAlexaff
B Adamowicz, T Manière, Vincent Déry, Étienne Désilets

Bibliographic record

VenueCase Reports in Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsHôpital Charles-Le MoyneUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineFine-needle aspirationEndoscopic ultrasoundRadiologyLymphPancreatitisSurgeryBiopsyPathology

Abstract

fetched live from OpenAlex

Endoscopic ultrasound fine-needle aspiration (EUS-FNA) is used to make a cytopathologic diagnosis of suspicious lesions located around the gastrointestinal tract. It is a safe technique with few complications. The most common complications of EUS-FNA are related to pancreatic lesions (pancreatitis, bleeding, and abdominal pain). Rare complications have been noted such as stent malfunction, air embolism, infection, neural and vascular injuries, and tumor cell seeding. There are very few studies examining equipment malfunctions. We report a case of needle fracture during the EUS-FNA of suspicious thoracic lymph nodes in a 79-year-old man investigated for unexplained weight loss.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.377
Teacher spread0.336 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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