Electron absorbed fractions of energy and<i>S</i>-values in an adult human skeleton based on µCT images of trabecular bone
Bibliographic record
Abstract
When the human body is exposed to ionizing radiation, among the soft tissues at risk are the active marrow (AM) and the bone endosteum (BE) located in tiny, irregular cavities of trabecular bone. Determination of absorbed fractions (AFs) of energy or absorbed dose in the AM and the BE represent one of the major challenges of dosimetry. Recently, at the Department of Nuclear Energy at the Federal University of Pernambuco, a skeletal dosimetry method based on µCT images of trabecular bone introduced into the spongiosa voxels of human phantoms has been developed and applied mainly to external exposure to photons. This study uses the same method to calculate AFs of energy and S-values (absorbed dose per unit activity) for electron-emitting radionuclides known to concentrate in skeletal tissues. The modelling of the skeletal tissue regions follows ICRP110, which defines the BE as a 50 µm thick sub-region of marrow next to the bone surfaces. The paper presents mono-energetic AFs for the AM and the BE for eight different skeletal regions for electron source energies between 1 keV and 10 MeV. The S-values are given for the beta emitters (14)C, (59)Fe, (131)I, (89)Sr, (32)P and (90)Y. Comparisons with results from other investigations showed good agreement provided that differences between methodologies and trabecular bone volume fractions were properly taken into account. Additionally, a comparison was made between specific AFs of energy in the BE calculated for the actual 50 µm endosteum and the previously recommended 10 µm endosteum. The increase in endosteum thickness leads to a decrease of the endosteum absorbed dose by up to 3.7 fold when bone is the source region, while absorbed dose increases by ∼20% when the beta emitters are in marrow.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".