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Record W2077897986 · doi:10.1115/1.4001864

A Novel Translational Total Body Irradiation Technique

2010· article· en· W2077897986 on OpenAlexafffund
Derek W. Brown, Kurt Knibutat, Nathan Edmonds, Daniel Tom, Leo Moriarty, Peter W Hanson, Mona Udowicz, Amjad Hussain, J. Eduardo Villarreal‐Barajas, Alana Hudson

Bibliographic record

VenueJournal of Medical Devices · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of Calgary
FundersCentre Hospitalier Universitaire de Québec
KeywordsInterlockIrradiationBeam (structure)Materials scienceRadiationOpticsBiomedical engineeringNuclear medicinePhysicsMedicineEngineeringStructural engineering

Abstract

fetched live from OpenAlex

A novel translating bed total body irradiation treatment delivery technique that employs dynamically shaped beams is presented. The patient is translated along the floor on a moving bed through a stationary radiation beam and the shape of the radiation beam is changed dynamically as the patient is moved through it, enabling compensation for local variations in patient thickness and tissue density. We demonstrate that the use of dynamically shaped beams results in greatly improved dose homogeneity compared with standard techniques, which use a single static beam shape. Along a representative dose profile through the lungs of a mock-human body, the maximum range of dose deviation from the average is 5.6% (from +2.7% to −2.9%) for the dynamic beam technique compared with 12.8% (from +3.6% to −9.2%) for the static beam technique. A novel, dual-interlock system that prevents bed motion when the radiation beam is stopped and stops the radiation beam when the bed motor is stopped has also been developed. The dual-interlock not only enhances the safety of the treatment but also ensures accuracy in the delivery of the treatment.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.829
Threshold uncertainty score0.999

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)0.0020.000

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 head0.007
GPT teacher head0.300
Teacher spread0.293 · 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.

Study designBench or experimental
Domainnot available
GenreMethods

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

Citations9
Published2010
Admission routes2
Has abstractyes

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