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Record W2007685895 · doi:10.1088/0031-9155/57/21/7147

Development of a novel multi-point plastic scintillation detector with a single optical transmission line for radiation dose measurement

2012· article· en· W2007685895 on OpenAlexaff
François Therriault‐Proulx, Louis Archambault, Luc Beaulieu, Sam Beddar

Bibliographic record

VenuePhysics in Medicine and Biology · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsHôtel-Dieu de QuébecCentre hospitalier universitaire de QuébecUniversité Laval
FundersNational Cancer Institute
KeywordsDetectorOpticsIonization chamberDosimetryDose profilePhysicsScintillationPhotonMaterials scienceNuclear medicineBeam (structure)IonIonization

Abstract

fetched live from OpenAlex

The goal of this study was to develop a novel multi-point plastic scintillation detector (mPSD) capable of measuring the dose accurately at multiple positions simultaneously using a single optical transmission line. A 2-point mPSD used a band-pass approach that included splitters, color filters and an EMCCD camera. The 3-point mPSD was based on a new full-spectrum approach, in which a spectrograph was coupled to a CCD camera. Irradiations of the mPSDs and of an ion chamber were performed with a 6 MV photon beam at various depths and lateral positions in a water tank. For the 2-point mPSD, the average relative differences between mPSD and ion chamber measurements for the depth-dose were 2.4±1.6% and 1.3±0.8% for BCF-60 and BCF-12, respectively. For the 3-point mPSD, the average relative differences over all conditions were 2.3±1.1%, 1.6±0.4% and 0.32±0.19% for BCF-60, BCF-12 and BCF-10, respectively. This study demonstrates the practical feasibility of mPSDs. This type of detector could be very useful for pre-treatment quality assurance applications as well as an accurate tool for real-time in vivo dosimetry.

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)0.001
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.202
GPT teacher head0.380
Teacher spread0.178 · 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
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

Citations52
Published2012
Admission routes1
Has abstractyes

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