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Record W4287753911 · doi:10.5281/zenodo.3903294

Determination of consensus kQ values for megavoltage photon beams for the update of IAEA TRS-398

2020· article· en· W4287753911 on OpenAlexaff
Pedro Andreo, D T Burns, Ralf‐Peter Kapsch, M McEwen, Stanislav Vatnitsky, C.E. Andersen, Facundo Ballester, Jorge Borbinha, F Delaunay, Paolo Francescon, M D Hanlon, Lalageh Mirzakhanian, Bryan Muir, Jarkko Ojala, C P Oliver, M. Pimpinella, Massimo Pinto, Leon de Prez, Jan Seuntjens, L Sommier, P. Teles, Joonas Tikkanen, J. Vijande, Klemens Zink

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsMcGill UniversityNational Research Council Canada
Fundersnot available
KeywordsPhotonMedical physicsNuclear medicineNuclear physicsPhysicsMedicineOptics

Abstract

fetched live from OpenAlex

The IAEA is currently coordinating a multi-year project to update the TRS-398 Code of Practice for the dosimetry of external beam radiotherapy based on standards of absorbed dose to water. One major aspect of the project is the determination of new beam quality correction factors, k<sub>Q</sub>, for megavoltage photon beams consistent with developments in radiotherapy dosimetry and technology since the publication of TRS-398 in 2000. Specifically, all values must be based on, or consistent with, the key data of ICRU Report 90. Data sets obtained from Monte Carlo (MC) calculations by advanced users and measurements at primary standards laboratories have been compiled for 23 cylindrical ionization chamber types, consisting of 725 MC-calculated and 179 experimental data points. These have been used to derive consensus k<sub>Q</sub> values as a function of the beam quality index TPR20,10 with a combined standard uncertainty of 0.6%. Mean values of MC-derived chamber-specific f<sub>ch</sub> factors for cylindrical and plane-parallel chamber types in <sup>60</sup>Co beams have also been obtained with an estimated uncertainty of 0.4%.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.259
Teacher spread0.226 · 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.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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