A MONTE CARLO STUDY OF SIMULATED MEASUREMENTS OF RADIONUCLIDES IN BONE
Bibliographic record
Abstract
When measuring the internally deposited activity in the bone of a subject, the placement of the detector is critical. This study reports the simulated counting efficiencies for three counting geometries, the skull, knee and shin, using 13 different voxel phantoms. It shows that the range of counting efficiencies for a given geometry is large for the studied phantoms, especially at low energies. Skull counting offers higher efficiency for low energies such as the 17 keV compared to knee counting or shin counting, but this advantage disappears when the energy is higher such as at 185 keV. This work also shows that the calibration phantom may greatly impact the accuracy of the activity estimate in bone counting, with uncertainties increasing greatly as the photon energy is reduced. Estimating the activity of a radionuclide in bone from direct counting has large uncertainties, and the dose calculated from a skeleton measurement would need careful analysis and, if possible, supporting data from other bioassay measurements.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".