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Record W2806968089 · doi:10.1002/mp.13025

Technical Note: Minimizing geometrical uncertainties of cylindrical well‐type ionization chamber measurements: There is an optimal chamber length

2018· article· en· W2806968089 on OpenAlexaff
Amir Keyvanloo, Hans‐S. Jans

Bibliographic record

VenueMedical Physics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIonization chamberSensitivity (control systems)Position (finance)IonizationRange (aeronautics)BrachytherapyMathematicsPhysicsMaterials scienceIonEngineeringElectronic engineering

Abstract

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PURPOSE: The response of well-type ionization chambers used, for example, in brachytherapy and nuclear medicine, depends on the location of the source. In cases where the source length is variable (typically in nuclear medicine), it is also dependent on length of the source. Here, the combined effect on chamber sensitivity of both source position and length is investigated in detail. This analysis is important if nominal values for source location and length are prescribed as (arbitrary but fixed) values in order to precisely define a chamber's sensitivity. During measurement, the actual values for source location and length can deviate from the nominal ones, altering sensitivity and thus giving rise to measurement uncertainties which, in turn, directly affect the doses administered to patients. Our aim is to investigate these uncertainties and minimize them with an optimized ion chamber design. METHODS: An analytical model for the chamber response is used to describe the variation of chamber sensitivity with respect to the two parameters, source position and length. The influence of the relative magnitude of uncertainty in both parameters is also accounted for. The effect of their combined variation on chamber sensitivity is required to be minimal and, employing differential geometry tools, a relationship is derived between them and the optimal height of the ionization chamber's sensitive volume. RESULTS: This relationship provides the chamber height h which minimizes its response variation for given nominal value of source location (quantified as insertion depth d) and prescribed source length l: h=2d-ρ(ρ)l, where ρ = δd/δl is defined as the quotient of uncertainty in insertion depth, δd, and uncertainty in source length, δl, and ρρ=4/9+ρ21+4ρ2, so that the optimal ionization chamber length varies between h=2d-12l and h=2d-23l. Alternatively, if h is given, suitable combinations of d and l can be deduced. CONCLUSIONS: The analysis presented here provides a tool for reducing the uncertainty budget of any cylindrically designed ionization chambers utilized for measuring extended on-axis sources. In particular, these results can be applied to a calibration-type ionization chamber design recently proposed for the cross-calibration of unsealed radionuclides.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.315
Teacher spread0.284 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2018
Admission routes1
Has abstractyes

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