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Record W4408793010 · doi:10.1136/bmjonc-2025-000745

Does radiation-induced lymphocytopenia matter? Developing a radiotherapy dosimetric strategy for immune preservation and improved survival

2025· letter· en· W4408793010 on OpenAlexaff
Mohammed Abdul-Latif, John Conibear, Niluja Thiruthaneeswaran, Y. Tsang

Bibliographic record

VenueBMJ Oncology · 2025
Typeletter
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsLymphocytopeniaRadiation therapyMedicineRadiologyImmunologyLymphocyte

Abstract

fetched live from OpenAlex

Globally, around half of all patients with cancer require radiotherapy as a part of their multimodality cancer treatment.1 Despite its important role in optimising cancer outcomes, its systemic immunological consequences, particularly radiation-induced lymphocytopenia, can pose a significant challenge and be associated with poorer treatment outcomes that impact the overall survival.

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)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.018
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0180.013
Insufficient payload (model declined to judge)0.0050.004

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 head0.033
GPT teacher head0.367
Teacher spread0.334 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2025
Admission routes1
Has abstractyes

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Same venueBMJ OncologySame topicEffects of Radiation ExposureFrench-language works237,207