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Diffuse Bone Marrow Uptake on F-18 FDG PET in Patients With Myelodysplastic Syndromes

2006· article· en· W1976409743 on OpenAlexaff
Kentaro Inoue, Ken Okada, Hideo Harigae, Yasuyuki Taki, Ryoi Goto, Shigeo Kinomura, Shunsuke Kato, Tomohiro Kaneta, Hiroshi Fukuda

Bibliographic record

VenueClinical Nuclear Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicHematological disorders and diagnostics
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsMedicineBone marrowMyelodysplastic syndromesHaematopoiesisPathologyStem cell

Abstract

fetched live from OpenAlex

It is well known that hematopoietic cytokine stimulation can cause diffuse increase of FDG accumulation in bone marrow on PET imaging, which simulates that seen in patients with bone marrow metastases. However, diffuse bone marrow FDG uptake can be caused by other etiologies. We report 2 patients who did not have a history of hematopoietic cytokine stimulation. The FDG PET images showed diffuse bone marrow FDG uptake, and the patients were diagnosed as having myelodysplastic syndromes. These cases demonstrate that diffuse FDG uptake by bone marrow can suggest neoplastic disease of the hematopoietic tissues.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.305
Teacher spread0.274 · 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 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

Citations42
Published2006
Admission routes1
Has abstractyes

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