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Record W1996126815 · doi:10.1097/rlu.0b013e3181e4dd44

Pulmonary Light and Heavy Chain Deposition Disease

2010· article· en· W1996126815 on OpenAlexaff
William Makis, Vilma Derbekyan, Javier-A. Novales-Diaz

Bibliographic record

VenueClinical Nuclear Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging and Pathology Studies
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineNodule (geology)MalignancyLungRespiratory diseaseLung diseaseRadiologySolitary pulmonary nodulePulmonary diseasePathologyNuclear medicineInternal medicine

Abstract

fetched live from OpenAlex

A 64-year-old man with a history of smoking and asbestos exposure was referred for an F-18 FDG PET/CT, to evaluate multiple growing lung nodules that had been found incidentally on prior chest CTs. The PET/CT showed multiple hypermetabolic nodules in both the lungs, with varying intensity of FDG uptake, raising the suspicion of multifocal malignancy. Wedge resections of the right lung were done to remove the 2 most hypermetabolic nodules, and histologic evaluation revealed pulmonary light and heavy chain deposition disease. A follow-up PET/CT performed 1 year later showed another slowly growing nodule in the left lung with a significant increase in F-18 FDG uptake. Only 22 cases of pulmonary light chain deposition disease have been reported in the literature. This is a report of F-18 FDG uptake in nodules of pulmonary light chain deposition disease. These nodules can grow in size and can show increased F-18 FDG uptake on follow-up studies, mimicking a growing lung malignancy.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.337
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.363
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 teacher head, 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

Citations7
Published2010
Admission routes1
Has abstractyes

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