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Record W2896331467 · doi:10.1097/rlu.0000000000002301

18F-DCFPyL PET/CT in Oncocytoma

2018· article· en· W2896331467 on OpenAlexaff
Jeremy Li, Richard Huan Xu, Chun K. Kim, François Bénard, Anil Kapoor, Glenn Bauman, Katherine Zukotynski

Bibliographic record

VenueClinical Nuclear Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British ColumbiaLondon Health Sciences CentreMcMaster University
Fundersnot available
KeywordsMedicineProstate cancerLymph nodePathologyBiopsyPET-CTAvidityOncocytomaAntigenCancerRadiologyPositron emission tomographyInternal medicineImmunohistochemistry

Abstract

fetched live from OpenAlex

A 76-year-old man with biochemical failure after primary radiotherapy for prostate cancer had no malignant disease detected on Tc-MDP bone scan and diagnostic CT. Prostate-specific membrane antigen (PSMA), a type II transmembrane glycoprotein, is overexpressed in prostate cancer cells. The PSMA-targeted F-DCFPyL PET/CT demonstrated lymph node disease and photopenic defects in the left kidney associated with a cyst and biopsy-proven oncocytoma. Prostate-specific membrane antigen is expressed in the neovasculature of several solid tumors. It has been reported that PSMA expression is seen in approximately 50% of oncocytoma versus 76% of clear cell renal carcinomas. Biopsy confirmation is needed regardless of F-DCFPyL avidity.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.001
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 head0.115
GPT teacher head0.477
Teacher spread0.362 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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