MétaCan
Menu
Back to cohort
Record W2041986914 · doi:10.1088/0031-9155/54/17/017

A comprehensive system for dosimetric commissioning and Monte Carlo validation for the small animal radiation research platform

2009· article· en· W2041986914 on OpenAlexaff
E. Tryggestad, Michael Armour, Iulian Iordachita, Frank Verhaegen, John Wong

Bibliographic record

VenuePhysics in Medicine and Biology · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsMcGill University
FundersNational Cancer InstituteNovell
KeywordsMonte Carlo methodRangingDosimetryRadiationBeam (structure)Range (aeronautics)PhysicsComputational physicsOpticsNuclear medicineMedical physicsComputer scienceMathematicsEngineeringMedicineStatisticsAerospace engineeringTelecommunications

Abstract

fetched live from OpenAlex

Our group has constructed the small animal radiation research platform (SARRP) for delivering focal, kilo-voltage radiation to targets in small animals under robotic control using cone-beam CT guidance. The present work was undertaken to support the SARRP's treatment planning capabilities. We have devised a comprehensive system for characterizing the radiation dosimetry in water for the SARRP and have developed a Monte Carlo dose engine with the intent of reproducing these measured results. We find that the SARRP provides sufficient therapeutic dose rates ranging from 102 to 228 cGy min(-1) at 1 cm depth for the available set of high-precision beams ranging from 0.5 to 5 mm in size. In terms of depth-dose, the mean of the absolute percentage differences between the Monte Carlo calculations and measurement is 3.4% over the full range of sampled depths spanning 0.5-7.2 cm for the 3 and 5 mm beams. The measured and computed profiles for these beams agree well overall; of note, good agreement is observed in the profile tails. Especially for the smallest 0.5 and 1 mm beams, including a more realistic description of the effective x-ray source into the Monte Carlo model may be important.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.210

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 head0.321
GPT teacher head0.467
Teacher spread0.146 · 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 designOther design
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

Citations81
Published2009
Admission routes1
Has abstractyes

Explore more

Same venuePhysics in Medicine and BiologySame topicAdvanced Radiotherapy TechniquesFrench-language works237,207