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RADIATION QUALITY OF A TOMOTHERAPY PHOTON FAN BEAM

2004· article· en· W2047593270 on OpenAlexaff
Vitali Moiseenko, Mark Mulligan, Tomas Kron

Bibliographic record

VenueHealth Physics · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsTomotherapyPenumbraImaging phantomLinear particle acceleratorPhysicsMonte Carlo methodPhotonLaser beam qualityBeam (structure)Linear energy transferRadiationOpticsPhoton energyNuclear medicineMedical physicsRadiation therapyMedicineLaserMathematicsRadiologyStatistics

Abstract

fetched live from OpenAlex

Tomotherapy, a novel radiotherapy technique, uses narrow fan beams for cancer patient treatment. Photon energy spectra for a rectangular 10 x 1 cm2 photon beam were analyzed in central axis and penumbra regions at depths of 3 to 10 cm in a water phantom. A 6 MV beam of a Varian 2100C/D Linear Accelerator was modeled using BEAM99 Monte Carlo calculations to simulate energy transport in a water phantom. Arrays of 4 x 2 mm2 scoring regions were arranged to cover the central axis and penumbra areas. Radiation quality factors were calculated based on dose-mean linear energy transfer. Although there appears to be a trend towards higher quality factor values in the penumbra area, this change is fairly small, at most 3% in penumbra region. We conclude that change in radiation quality is not likely to be an issue in a tomotherapeutic approach when 6 MV x rays are used.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0030.000

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 head0.026
GPT teacher head0.379
Teacher spread0.353 · 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 designBench or experimental
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

Citations9
Published2004
Admission routes1
Has abstractyes

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