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THE LLNL VOXEL PHANTOM: COMPARISON WITH THE PHYSICAL PHANTOM AND PREVIOUS VIRTUAL PHANTOMS

2007· article· en· W2021643529 on OpenAlex
Gary H. Kramer, Kevin Capello, Jeremy Sung

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

VenueHealth Physics · 2007
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsHealth Canada
Fundersnot available
KeywordsImaging phantomVoxelMonte Carlo methodPhysicsMedical physicsComputer scienceNuclear medicineOpticsComputer visionMathematicsMedicineStatistics

Abstract

fetched live from OpenAlex

The Human Monitoring Laboratory has created a voxel phantom from computer tomography scans of the Lawrence Livermore National Laboratory (LLNL) torso phantom for use in Monte Carlo simulations. The voxel phantom has been compared to the previously developed mathematical phantom using Monte Carlo simulations and both virtual phantoms have been compared to physical measurement of the LLNL phantom. The voxel phantom agreed well with the others, except at very low photon energies (i.e., 17.5 keV), with predicted counting efficiencies being within 2% of the counting efficiencies from the other two phantoms at 59.5 keV and above. The mathematical phantom performs similarly to the voxel phantom, but much faster, so it is an excellent alternative if computer power is lacking. The voxel phantom of the LLNL phantom is available from the authors, on request.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.023
GPT teacher head0.360
Teacher spread0.337 · 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