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Record W2088691849 · doi:10.1088/0031-9155/50/20/n02

A software tool for 2D/3D visualization and analysis of phase-space data generated by Monte Carlo modelling of medical linear accelerators

2005· article· en· W2088691849 on OpenAlexfundno aff
T Neicu, Khaled Aljarrah, Steve Jiang

Bibliographic record

VenuePhysics in Medicine and Biology · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsMonte Carlo methodComputer scienceSoftwareVisualizationFluencePhase spaceEnergy (signal processing)Computer graphics (images)Linear particle acceleratorDomain (mathematical analysis)Computational scienceComputational physicsAlgorithmBeam (structure)PhysicsOpticsData miningMathematicsStatisticsMathematical analysis

Abstract

fetched live from OpenAlex

A computer program has been developed for novel 2D/3D visualization and analysis of the phase-space parameters of Monte Carlo simulations of medical accelerator radiation beams. The software is written in the IDL language and reads the phase-space data generated in the BEAMnrc/BEAM Monte Carlo code format. Contour and colour-wash plots of the fluence, mean energy, energy fluence, mean angle, spectra distribution, energy fluence distribution, angular distribution, and slices and projections of the 3D ZLAST distribution can be calculated and displayed. Based on our experience of using it at Massachusetts General Hospital, the software has proven to be a useful tool for analysis and verification of the Monte Carlo generated phase-space files. The software is in the public domain.

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)0.002
metaresearch head score (Gemma)0.004
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: Software · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0440.011

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 head0.178
GPT teacher head0.447
Teacher spread0.269 · 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
GenreSoftware

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

Citations1
Published2005
Admission routes1
Has abstractyes

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