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Record W2999105460 · doi:10.1088/1361-6560/ab6953

Experimental validation of recommended <i>msr</i> -correction factors for the calibration of Leksell Gamma Knife <sup>®</sup> Icon <sup>tm</sup> unit following IAEA TRS-483

2020· article· en· W2999105460 on OpenAlexafffund
Lalageh Mirzakhanian, Arman Sarfehnia, Jan Seuntjens

Bibliographic record

VenuePhysics in Medicine and Biology · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of TorontoMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCalibrationKermaProtocol (science)Context (archaeology)DosimetryMedical physicsNuclear medicinePhysicsNuclear engineeringComputer scienceMedicineEngineering

Abstract

fetched live from OpenAlex

(LGK) (despite the publication of the AAPM TG-51 protocol). However, this protocol is based on the air-kerma standards requiring an elaborate conversion process resulting in an increase in the possibility of errors in the clinic. The International Atomic Energy Agency (IAEA) Technical Reports Series (TRS)-483 Code of Practice provides new recommendations on the dosimetry of small static fields and correction factor data for the calibration of the LGK unit. The purpose of this study is to experimentally validate previously calculated [Formula: see text] factors for the calibration of the LGK Perfexion/Icon unit in the context of the TRS-483 protocol. An experimental comparison between three protocols (TG-51, TG-21 and TRS-483 with the aforementioned correction factors) for calibration of the LGK unit is provided. Dose-rate measurements were performed on a LGK Icon unit using three ionization chambers and three phantoms with different orientations of the chambers with respect to the LGK unit. The dose rate was determined following the three calibration protocols. The standard deviation on the mean dose rate over all phantoms and chambers in different orientations determined using TG-51, TG-21 and TRS-483 protocols were 0.9%, 0.5% and 0.4%, respectively. The mean dose rate calculated using TG-51 protocol was 1.6% and 1.2% lower comparing to the TG-21 and TRS-483 protocols respectively. Applying the [Formula: see text] values calculated in Mirzakhanian et al (2018) to the measured dose rates in LGK unit for all chambers and phantoms resulted in dose rates that are consistent to within 0.4%. The TRS-483 protocol improves the consistency of the results especially when the chamber was positioned in different orientations with respect to the LGK (from 1.6% when using TG-51 or TG-21 protocols to 0.2% when using TRS-483 protocol) since the other protocols do not correct for the different chamber orientations.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.120
GPT teacher head0.370
Teacher spread0.250 · 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 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

Citations6
Published2020
Admission routes2
Has abstractyes

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