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Record W2726541308 · doi:10.1002/mp.12463

Electron beam water calorimetry measurements to obtain beam quality conversion factors

2017· article· en· W2726541308 on OpenAlexaffabout
Bryan Muir, C. D. Cojocaru, M McEwen, C. K. Ross

Bibliographic record

VenueMedical Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsNational Research Council Canada
FundersInternational Atomic Energy Agency
KeywordsIonization chamberCalorimeter (particle physics)CalorimetryIonBeam (structure)CalibrationMaterials scienceIon beamIonizationLaser beam qualityLinear particle acceleratorAtomic physicsChemistryAnalytical Chemistry (journal)OpticsPhysics

Abstract

fetched live from OpenAlex

Purpose To provide results of water calorimetry and ion chamber measurements in high‐energy electron beams carried out at the National Research Council Canada ( NRC ). There are three main aspects to this work: (a) investigation of the behavior of ionization chambers in electron beams of different energies with focus on long‐term stability, (b) water calorimetry measurements to determine absorbed dose to water in high‐energy beams for direct calibration of ion chambers, and (c) using measurements of chamber response relative to reference ion chambers, determination of beam quality conversion factors, k Q , for several ion chamber types. Methods Measurements are made in electron beams with energies between 8 MeV and 22 MeV from the NRC Elekta Precise clinical linear accelerator. Ion chamber measurements are made as a function of depth for cylindrical and plane‐parallel ion chambers over a period of five years to investigate the stability of ion chamber response and for indirect calibration. Water calorimetry measurements are made in 18 MeV and 22 MeV beams. An insulated enclosure with fine temperature control is used to maintain a constant temperature (drifts less than 0.1 mK /min) of the calorimeter phantom at 4°C to minimize effects from convection. Two vessels of different designs are used with calibrated thermistor probes to measure radiation induced temperature rise. The vessels are filled with high‐purity water and saturated with H 2 or N 2 gas to minimize the effect of radiochemical reactions on the measured temperature rise. A set of secondary standard ion chambers are calibrated directly against the calorimeter. Finally, several other ion chambers are calibrated in the NRC 60 Co reference field and then cross‐calibrated against the secondary standard chambers in electron beams to realize k Q factors. Results The long‐term stability of the cylindrical ion chambers in electron beams is better (always %) than plane‐parallel chambers (0.2% to 0.4%). Calorimetry measurements made at 22 MeV with two different vessel geometries are consistent within 0.2% after correction for the vessel perturbation. Measurements of absorbed dose calibration coefficients for the same secondary standard chamber separated in time by 10 yr are within 0.2%. Drifts in linac output that would affect the transfer of the standard are mitigated to the 0.1% level by performing daily ion chamber normalization measurements. Calibration coefficients for secondary standard ion chambers can be achieved with uncertainties less than 0.4% (k = 1) in high‐energy electron beams. The additional uncertainty in deriving calibration coefficients for well‐behaved chambers indirectly against the secondary standard reference chambers is negligible. The k Q factors measured here differ by up to 1.3% compared to those in TG ‐51, an important change for reference dosimetry measurements. Conclusions The measurements made here of k Q factors for eight plane‐parallel and six cylindrical ion chambers will impact future updates of reference dosimetry protocols by providing some of the highest quality measurements of this crucial dosimetric parameter.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.686

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 science0.0010.000
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 head0.037
GPT teacher head0.347
Teacher spread0.309 · 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

Citations19
Published2017
Admission routes2
Has abstractyes

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