MétaCan
Menu
Back to cohort
Record W3184663704 · doi:10.3390/s21155157

Dosimetric Application of Phosphorus Doped Fibre for X-ray and Proton Therapy

2021· article· en· W3184663704 on OpenAlexaff
Olugbenga J. Olusoji, Crystal Penner, C. Bélanger-Champagne, Wern Kam, Michael Martyn, Peter Woulfe, Cornelia Hoehr, Sinéad O’Keeffe

Bibliographic record

VenueSensors · 2021
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsDosimeterDosimetryMaterials scienceBragg peakLinear energy transferProton therapyPhotonAttenuationProtonRadiationDopingRadiochemistrySaturation (graph theory)OpticsRadiation therapyNuclear medicineOptoelectronicsChemistryPhysicsNuclear physicsMedicine

Abstract

fetched live from OpenAlex

Phosphorous-doped silica optical fibres with a core diameter of 4 µm were tested in X-ray and proton fields for application in cancer therapy dosimetry. Specifically, the radiation-induced attenuation was investigated in terms of linearity in deposited dose in 15 MV and 6 MV photons and 74 MeV protons, as well as Bragg-peak detection along the proton track. Fibres were found to demonstrate linear relative dose response in both radiation modalities, but possible saturation did occur at the high linear energy transfer of the Bragg peak. This demonstrates the possibility to use these fibres as a relative dosimeter for radiation therapy applications.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.009
GPT teacher head0.218
Teacher spread0.208 · 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 designBench or experimental
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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueSensorsSame topicPhotonic Crystal and Fiber OpticsFrench-language works237,207