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Record W2020719320 · doi:10.1118/1.2402342

Technical note: Overprediction of dose with default PRESTA‐I boundary crossing in DOSXYZnrc and BEAMnrc

2007· article· en· W2020719320 on OpenAlexaff
B. R. B. Walters, I. Kawrakow

Bibliographic record

VenueMedical Physics · 2007
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsBoundary (topology)ElectronImaging phantomPhotonPhysicsVoxelScatteringCharged particleAtomic physicsParticle (ecology)Computational physicsNuclear physicsIonOpticsComputer scienceMathematicsMathematical analysisQuantum mechanics

Abstract

fetched live from OpenAlex

Use of the PRESTA-I (current default) boundary crossing algorithm for charged particles in DOSXYZnrc and BEAMnrc is shown to result in dose overprediction by up to 2.5% in photon and electron beams (less in high-energy electron beams). The effect is most pronounced when charged particle equilibrium does not exist or when the phantom is not divided into uniform voxels throughout. As a result, the default boundary crossing algorithm in BEAMnrc will be changed to "exact" (single scattering).

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: none
Teacher disagreement score0.759
Threshold uncertainty score0.393

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 studies0.0000.001
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 head0.013
GPT teacher head0.329
Teacher spread0.316 · 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
Published2007
Admission routes1
Has abstractyes

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