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Record W2145804736 · doi:10.1088/0031-9155/49/3/004

 Tongue-and-groove  effect in intensity modulated radiotherapy with static multileaf collimator fields

2004· article· en· W2145804736 on OpenAlexaff
W. Que, Jong Kung, Jianrong Dai

Bibliographic record

VenuePhysics in Medicine and Biology · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMultileaf collimatorGroove (engineering)Intensity (physics)TongueCollimatorSliding window protocolIntensity modulationComputer scienceRadiation therapyMathematicsMaterials scienceOpticsMedicineWindow (computing)PhysicsSurgeryRadiation treatment planning

Abstract

fetched live from OpenAlex

The 'tongue-and-groove problem' in step-and-shoot delivery of intensity modulated radiotherapy is investigated. A 'tongue-and-groove' index (TGI) is introduced to quantify the 'tongue-and-groove' effect in step-and-shoot delivery. Four different types of leaf sequencing methods are compared. The sliding window method and the reducing level method use the same number of field segments to deliver the same intensity map, but the TGI is much less for the reducing level method. The leaf synchronization method of Van Santvoort and Heijmen fails in step-and-shoot delivery, but a new method inspired by the method of Van Santvoort and Heijmen is shown to eliminate 'tongue-and-groove' underdosage completely.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score0.427

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 head0.043
GPT teacher head0.360
Teacher spread0.318 · 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 designObservational
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

Citations37
Published2004
Admission routes1
Has abstractyes

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