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Record W4309530783 · doi:10.1016/j.ctro.2022.11.010

TORPEdO: A phase III trial of intensity-modulated proton beam therapy versus intensity-modulated radiotherapy for multi-toxicity reduction in oropharyngeal cancer

2022· article· en· W4309530783 on OpenAlexaff
David Thomson, Clare Cruickshank, Helen Baines, Russell Banner, Matthew Beasley, Guy Betts, Helen Bulbeck, Frances Charlwood, Judith Christian, Matthew Clarke, Bernadette Foran, Callum Gillies, Clare Griffin, Jarrod J. Homer, Johannes A. Langendijk, Lip Wai Lee, James C. Lester, Matthew Lowe, Andrew McPartlin, Elizabeth Miles, Christopher M. Nutting, Nachi Palaniappan, Robin Prestwich, James Price, Clare Roberts, Justin Roe, Ramkumar Shanmugasundaram, Rita Simões, Anna Thompson, Catharine West, Lorna Rachel Maven Wilson, Jane Wolstenholme, Emma Hall

Bibliographic record

VenueClinical and Translational Radiation Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer Centre
FundersDepartment of Health and Social CareCancer Research UKUniversity College London Hospitals NHS Foundation TrustNational Institute for Health and Care ResearchNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
KeywordsMedicineIntensity (physics)ToxicityRadiation therapyReduction (mathematics)Beam (structure)Proton therapyIntensity modulationOncologyPhase (matter)Nuclear medicineInternal medicineOpticsPhase modulationChemistryPhysicsMathematics

Abstract

fetched live from OpenAlex

•There is a lack of prospective level I evidence for the use of PBT for most adult cancers including oropharyngeal squamous cell carcinoma (OPSCC).•TORPEdO is the UK's first PBT clinical trial and aims to determine the benefits of PBT for OPSCC.•Training and support has been provided before and during the trial to reduce variations of contouring and radiotherapy planning.•There is a strong translational component within TORPEdO. Imaging and physics data along with blood, tissue collection will inform future studies in refining patient selection for IMPT.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.146
GPT teacher head0.474
Teacher spread0.328 · 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 designRandomized trial
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

Citations22
Published2022
Admission routes1
Has abstractyes

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