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Record W2114562203 · doi:10.1093/rpd/ncr485

A comparison of organ doses between mathematical and voxel phantoms with the DS02 photon fluences

2012· article· en· W2114562203 on OpenAlex
J. Chen, G.D. Kerr, Harry M. Cullings

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

VenueRadiation Protection Dosimetry · 2012
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsHealth Canada
Fundersnot available
KeywordsGeorge (robot)ChenLibrary scienceMedical physicsVoxelArt historyNuclear medicineComputer sciencePhysicsMedicineArtificial intelligenceArtBiology

Abstract

fetched live from OpenAlex

The purpose of this study is to quantify dosimetric differences if modern sophisticated voxel phantoms were used in the dosimetry system DS02 rather than the mathematical phantoms. The mathematical models (ADAM and EVA) and voxel phantoms (REX and REGINA) developed in Germany allow a useful comparison as they are very close in body weight, body height and organ masses. In this study, organ doses are calculated with published fluence-to-absorbed-dose conversion coefficients derived from those two model sets for unidirectional plane beam irradiation geometries, with DS02 photon energy spectra at various distances from the hypocentre in Hiroshima. Results showed that organ doses from mathematical models generally agree well with those from voxel phantoms except for a few organs at lateral irradiation geometries and eye lenses at antero-posterior irradiation, even though there were significant differences between the two phantom sets and various uncertainties in dose calculations.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.304

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 head0.031
GPT teacher head0.328
Teacher spread0.297 · 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