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Record W4366768299 · doi:10.7759/cureus.37980

A Rare Case of Recurrent Cutaneous Non-Hodgkin’s Lymphoma in the Extremity: Long-Term Follow-Up and Review of the Literature Written With the Assistance of ChatGPT

2023· article· en· W4366768299 on OpenAlexaff
Taylor Dejong, Jeewanjit Gill, Selay Lam, Sarah Freiburger, Michael Lock

Bibliographic record

VenueCureus · 2023
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversity of OttawaWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineLymphomaPresentation (obstetrics)Chronic lymphocytic leukemiaHodgkin lymphomaComplete responseCase presentationRadiation therapyDermatologySurgeryChemotherapyLeukemiaInternal medicine

Abstract

fetched live from OpenAlex

Cutaneous involvement of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) is uncommon. We report on a 71-year-old male with a history of CLL of the skin in the distal extremities. The patient presented with eruptions of new lesions on the toes of his feet bilaterally, causing significant pain that limited his mobility. Cutaneous involvement of CLL is a rare presentation, and management recommendations are largely based on case reports with limited follow-up. Furthermore, assessing the duration of response, response rates, and correct sequencing of treatment is difficult due to variable use and doses of treatment. The case was treated in 2001 when newer systemic treatments were not available. Therefore, the results can also be directly related to local treatments. Based on a literature review and this case, this report provides insight into the benefits and risks of local treatment for cutaneous involvement of CLL in the extremities and how radiation can be sequenced with other options such as surgical excision and chemotherapy.

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 categoriesResearch integrity
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 score0.998
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.020
GPT teacher head0.307
Teacher spread0.287 · 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.

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
Published2023
Admission routes1
Has abstractyes

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