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Record W1992995014 · doi:10.1177/1534735409356981

Can the Therapeutic Gain of Radiotherapy Be Increased by Concurrent Administration of Asian Botanicals?

2009· review· en· W1992995014 on OpenAlexaff
Stephen M. Sagar

Bibliographic record

VenueIntegrative Cancer Therapies · 2009
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPlant-based Medicinal Research
Canadian institutionsMcMaster UniversityJuravinski Cancer Centre
Fundersnot available
KeywordsRadiation therapyMedicineTherapeutic effectTraditional Chinese medicineTherapeutic indexPharmacologyCancer researchClinical trialTissue repairInternal medicinePathologyDrugBiomedical engineering

Abstract

fetched live from OpenAlex

Therapeutic gain by radiotherapy can be achieved through improved targeting, selectively sensitizing malignant cells, or protecting normal tissue. The majority of synthetic chemical radiation sensitizers and normal tissue protectors have proved to be too toxic at effective clinical doses. However, Asian botanicals (from both Chinese and Ayurvedic medicine) are being evaluated for their ability to improve therapeutic gain through the modulation of reactive oxygen species. An increase in the efficacy of radiotherapy on tumor tissue allows a reduction in the dose applied to normal tissues. In addition, some botanicals may selectively protect normal tissue or increase its repair following radiation therapy. The results are promising enough to consider clinical trials.

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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.223
GPT teacher head0.541
Teacher spread0.318 · 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

Citations13
Published2009
Admission routes1
Has abstractyes

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