MétaCan
Menu
Back to cohort
Record W1519882095 · doi:10.1120/jacmp.v12i3.3432

Influence of electron density spatial distribution and X‐ray beam quality during CT simulation on dose calculation accuracy

2011· article· en· W1519882095 on OpenAlexaff
Ahmad Nobah, Belal Moftah, Nada Tomic, Slobodan Dević

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsHounsfield scaleMonte Carlo methodPhotonCathode rayElectronComputational physicsBeam (structure)Materials scienceX-rayNuclear medicineElectron densityRadiationPhysicsDistribution (mathematics)Photon energyOpticsComputed tomographyMathematicsNuclear physicsStatisticsMedicineRadiology

Abstract

fetched live from OpenAlex

Impact of the various kVp settings used during computed tomography (CT) simulation that provides data for heterogeneity corrected dose distribution calculations in patients undergoing external beam radiotherapy with either high-energy photon or electron beams have been investigated. The change of the Hounsfield Unit (HU) values due to the influence of kVp settings and geometrical distribution of various tissue substitute materials has also been studied. The impact of various kVp settings and electron density (ED) distribution on the accuracy of dose calculation in high-energy photon beams was found to be well within 2%. In the case of dose distributions obtained with a commercially available Monte Carlo dose calculation algorithm for electron beams, differences of more than 10% were observed for different geometrical setups and kVp settings. Dose differences for the electron beams are relatively small at shallow depths but increase with depth around lower isodose values.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.381
Teacher spread0.351 · 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 designObservational
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

Citations26
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Clinical Medical PhysicsSame topicAdvanced Radiotherapy TechniquesFrench-language works237,207