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Record W1983416412 · doi:10.1088/0031-9155/55/16/s01

Two new DOSXYZnrc sources for 4D Monte Carlo simulations of continuously variable beam configurations, with applications to RapidArc, VMAT, TomoTherapy and CyberKnife

2010· article· en· W1983416412 on OpenAlexaff
Julio Lobo, I. Antoniu Popescu

Bibliographic record

VenuePhysics in Medicine and Biology · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of VictoriaBC Cancer AgencyUniversity of British Columbia
Fundersnot available
KeywordsTomotherapyMonte Carlo methodCyberknifeMultileaf collimatorCollimatorLinear particle acceleratorComputer scienceRotation (mathematics)Beam (structure)PhysicsRadiosurgerySimulationOpticsMathematicsRadiation therapyMedicineComputer vision

Abstract

fetched live from OpenAlex

We present two new Monte Carlo sources for the DOSXYZnrc code, which can be used to compute dose distributions due to continuously variable beam configurations. These sources support a continuously rotating gantry and collimator, dynamic multileaf collimator (MLC) motion, variable monitor unit (MU) rate, couch rotation and translation in any direction, arbitrary isocentre motion with respect to the patient and variable source-to-axis distance (SAD). These features make them applicable to Monte Carlo simulations for RapidArc, Elekta VMAT, TomoTherapy and CyberKnife. Unique to these sources is the synchronization between the motion in the DOSXYZnrc geometry and the motion within the linac head, represented by a shared library (either a BEAMnrc accelerator with dynamic component modules, or an external library). The simulations are achieved in single runs, with no intermediate phase space files.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.703
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.045
GPT teacher head0.372
Teacher spread0.326 · 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 designTheoretical or conceptual
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

Citations68
Published2010
Admission routes1
Has abstractyes

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