MétaCan
Menu
Back to cohort
Record W2471055795 · doi:10.1259/bjr.20160474

The changing paradigm of tumour response to irradiation

2016· review· en· W2471055795 on OpenAlexafffund
Rićhard P. Hill

Bibliographic record

VenueBritish Journal of Radiology · 2016
Typereview
Languageen
FieldMedicine
TopicCancer, Stress, Anesthesia, and Immune Response
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
FundersTerry Fox Foundation
KeywordsStromal cellBone marrowImmune systemCancer researchTumor microenvironmentTumour heterogeneityStem cellCancer cellBiologyRadiation therapyHypoxia (environmental)CancerPathologyMedicineImmunologyCell biologyChemistryInternal medicine

Abstract

fetched live from OpenAlex

Tumours contain multiple different cell populations, including cells derived from the bone marrow as well as cancer-associated fibroblasts and various stromal populations including the vasculature. The microenvironment of the tumour cells plays a significant role in the response of the tumour to radiation treatment. Low levels of oxygen (hypoxia) caused by the poorly organized vasculature in tumours have long been known to affect radiation response; however, other aspects of the microenvironment may also play important roles. This article reviews some of the old literature concerning tumour response to irradiation and relates this to current concepts about the role of the tumour microenvironment in tumour response to radiation treatment. Included in the discussion are the role of cancer stem cells, radiation damage to the vasculature and the potential for radiation to enhance immune activity against tumour cells. Radiation treatment can cause a significant influx of bone marrow-derived cell populations into both normal tissues and tumours. Potential roles of such cells may include enhancing vascular recovery as well as modulating immune reactivity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.311
Teacher spread0.290 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations35
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueBritish Journal of RadiologySame topicCancer, Stress, Anesthesia, and Immune ResponseFrench-language works237,207