THE LLNL VOXEL PHANTOM: COMPARISON WITH THE PHYSICAL PHANTOM AND PREVIOUS VIRTUAL PHANTOMS
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".