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Record W2023042056 · doi:10.1088/0031-9155/51/17/n02

Measurement for the MLC leaf velocity profile by considering the leaf leakage using a radiographic film

2006· article· en· W2023042056 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysics in Medicine and Biology · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor Technologies Research
Canadian institutionsGrand River HospitalPrincess Margaret Cancer CentreUniversity of TorontoUniversity of WaterlooUniversity Health Network
Fundersnot available
KeywordsCollimatorLeakage (economics)RadiographyEnhanced Data Rates for GSM EvolutionOpticsLine (geometry)Consistency (knowledge bases)Materials scienceNuclear medicineMathematicsPhysicsMedicineComputer scienceGeometryRadiologyComputer vision

Abstract

fetched live from OpenAlex

A method to measure the velocity profile of a multi-leaf collimator (MLC) leaf along its travel range using a radiographic film is reported by considering the intra-leaf leakage. A specific dynamic MLC field with leaves travelling from the field edge to the isocentre line was designed. The field was used to expose a radiographic film, which was then scanned, and the dose profile along the horizontal leaf axis was measured. The velocity at a sampling point on the film can be calculated by considering the horizontal distance between the sampling point and the isocentre line, dose at the sampling point, dose rate of the linear accelerator, the total leaf travel time from the field edge to isocentre line and the pre-measured dose rate of leaf leakage. With the leaf velocities and velocity profiles for all MLC leaves measured routinely, a comprehensive and simple QA for the MLC can be set up to test the consistency of the leaf velocity performance which is essential to the IMRT delivery using a sliding window technique.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.284

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 studies0.0000.001
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 head0.221
GPT teacher head0.360
Teacher spread0.139 · 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