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Record W1994797349 · doi:10.1118/1.1563663

Monte Carlo calculated correction factors for primary standards of air kerma

2003· article· en· W1994797349 on OpenAlexaffabout
D. W. O. Rogers, I. Kawrakow

Bibliographic record

VenueMedical Physics · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsKermaMonte Carlo methodDosimetryMedical physicsNuclear medicinePhysicsMedicineStatisticsMathematics

Abstract

fetched live from OpenAlex

Many laboratories with cavity chambers as primary standards for air kerma are considering using additional Monte Carlo calculated correction factors, in particular the correction for attenuation and scatter in the walls, Kwall, and possibly the correction for point of measurement, Kan. Standards labs also use Monte Carlo calculated Spencer-Attix stopping-power ratios for graphite to air. The purpose of this article is to investigate the sensitivity of these calculations to their details and to assign uncertainties to the calculated values. We also investigate the correction needed for the Canadian primary standard to account for a polystyrene insulator, Kcomp and find that it is quite large (1.0046 +/- 0.0017). The article shows that the values of correction factors are very robust and insensitive to most details of the calculations except the values of the underlying electron stopping powers which have a significant effect on the stopping-power ratio and on Kcomp. The 1% uncertainties on the photon cross-sections have a negligible effect on these correction factors except for Kcomp. As a result of these investigations, with no change in the stopping power data used, the Canadian primary standard of air kerma in a 60Co beam needs to be increased by 0.54%.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.840
Threshold uncertainty score0.475

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 head0.008
GPT teacher head0.282
Teacher spread0.274 · 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 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

Citations58
Published2003
Admission routes2
Has abstractyes

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