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Record W2020883575 · doi:10.1118/1.2965981

Sci‐Fri PM: Planning‐09: An EGSnrc investigation of ion chamber response to Co‐60 beams

2008· article· en· W2020883575 on OpenAlexaff
DJ La Russa, DWO Rogers

Bibliographic record

VenueMedical Physics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsIonization chamberRadiation treatment planningPhysicsIonNuclear medicineMedical physicsMedicineRadiologyRadiation therapyIonization

Abstract

fetched live from OpenAlex

The EGSnrc Monte Carlo code was evaluated for its ability to calculate the relative response of a variety of ion chambers to Co-60 beams as a means of justifying the use of this code in future investigations of cavity theory. EGSnrc calculations were compared to measurements with four separate ion chambers, which were each configured with several wall materials (ranging from plastic to lead) and cavity sizes (or cavity air pressures). The experimental results included measurements by Nilsson et al. in 1992, and experiments by Whyte, Attix et al. and Cormack and Johns in the mid-to-late 1950's designed to evaluate Spencer-Attix cavity theory. Experiments by Whyte involved measurements of the response per unit mass as a function of cavity air pressure for a large cylindrical chamber, whereas the other experiments consisted of measurements of the response per unit mass (or ionization current) as a function of the distance between the front and back wall (cavity height) of a plane-parallel chamber. EGSnrc calculations, which could account for the change in response associated with changes in wall material in most cases, were generally within 1-3% of experimental values, even for experimental data that required calculations of unreported wall corrections determined using experimental techniques. The ability of EGSnrc to accurately model these experiments, which showed variations up to 300%, confirms its suitability for detailed Monte Carlo studies of cavity theory.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.624

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 head0.029
GPT teacher head0.296
Teacher spread0.267 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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