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Record W2122010571 · doi:10.1124/mi.4.5.7

MECHANISMS OF RADIATION INJURY TO THE CENTRAL NERVOUS SYSTEM: IMPLICATIONS FOR NEUROPROTECTION

2004· review· en· W2122010571 on OpenAlexaff
C. Shun Wong

Bibliographic record

VenueMolecular Interventions · 2004
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoHealth Sciences Centre
FundersNational Cancer Institute
KeywordsNeuroprotectionCentral nervous systemProgrammed cell deathMedicineNeuroscienceMechanism (biology)ApoptosisApoptotic cell deathLimitingClonogenic assayRadiation injuryRadiation therapyBioinformaticsBiologySurgery

Abstract

fetched live from OpenAlex

The central nervous system (CNS) is a major dose-limiting organ in clinical radiotherapy (XRT). The underlying mechanisms of radiation-induced injury in this organ remain unclear. For many years, research has focused on identifying the major target cells of damage, and depletion of target cells due to reproductive or clonogenic cell death was believed to be the primary cause of tissue damage and organ failure. There is now an increasing body of data indicating that the response of the CNS after XRT is a continuous and interacting process. This review addresses some of the recent advances in our understanding of the mechanisms of CNS radiation damage. Specifically, the focus is on apoptotic cell death, and cell death and injury mediated by secondary damage. These potentially reversible components of the injury response provide important targets for neuroprotective interventions.

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)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.053
GPT teacher head0.357
Teacher spread0.305 · 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
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

Citations258
Published2004
Admission routes1
Has abstractyes

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