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Record W4402534146 · doi:10.1177/24741264241276602

Isolated Recurrence of Diffuse Large B-Cell Lymphoma Predominantly in the Iris and Ciliary Body

2024· article· en· W4402534146 on OpenAlexaff
Amit V. Mishra, Shangjun Jiang, Matthew Tennant, Mark E. Seamone

Bibliographic record

VenueJournal of VitreoRetinal Diseases · 2024
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsCiliary bodyIRIS (biosensor)Diffuse large B-cell lymphomaLymphomaMedicinePathologyOphthalmologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Purpose: To describe a single case of systemic lymphoma recurring in the iris and ciliary body. Methods: A retrospective case review was performed. Results: A 75-year-old woman presented to the retina service with an iris mass in the left eye. Her medical history was significant for previous systemic diffuse large B-cell lymphoma treated with systemic chemotherapy. Aqueous sampling was significant for recurrence of the disease. Local therapy with intravitreal (IVT) methotrexate was initiated. Although there was initial improvement, an increased interval between injections led to disease recurrence. External beam radiation to the left eye was then applied, leading to a complete clinical remission. Conclusions: Systemic lymphoma presenting in the iris is a rare manifestation that should be considered on the differential for an amelanotic iris lesion. Although monotherapy with IVT methotrexate did not control the ocular disease in this patient, subsequent external beam radiation resulted in complete clinical remission.

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)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.261
Teacher spread0.255 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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