LETTER TO THE EDITOR: THE ABSORPTION PROPERTIES OF LEAD-FREE GARMENTS FOR USE IN RADIATION PROTECTION
Bibliographic record
Abstract
Dear Editor, Çetin et al.'s paper(1) on the absorption properties of Pb-free garments is missing some important context. They state that Sample 4 materials assessed ‘were lighter than a 0.5 mm lead garment and provided superior radiation protection’, which is arguably not supported by their results. The most obvious criticism is that the Sample 4 materials were shown to have similar attenuation properties to a 0.36 mm thick Pb material at 100 kVp, which means it provides inferior, not superior, protection when compared to 0.5 mm thick Pb aprons. Perhaps the authors mean the Sample 4 material was superior because it provided slightly more protection than the minimum required thickness of 0.35 mm Pb at 100 kVp and were ‘30% lighter’ than the 0.5 mm Pb material. Also 30% lighter than 0.5 mm Pb aprons are 0.35 mm Pb aprons, as discussed by Jones and Wagner.(2) Comparing the mass of material equivalent to 0.36 mm Pb thickness with 0.5 mm thick Pb is hardly a fair comparison. For the Sample 4 material to be superior with this metric, these samples would need to weigh <0.36 mm thick Pb material. Pure Pb has a density of 11.34 g cm−3, so a 0.36 mm Pb shield of 1 m2 size would have a mass of 4.0824 kg m−2, compared to the Sample 4's mass of 4.0081 kg m−2. Using these numbers, the weight reduction of the Sample 4 material is 2%, instead of the 30% stated in the paper. While still a reduction, it is not a drastic reduction. Also of note is that these measurements were taken using the primary beam geometry, as recommended by Jones and Wagner.(2) However, Jones and Wagner also provided a caution about beam qualities used in the measurements, and warn against specifying Pb equivalency at a single kVp since ‘A garment may provide a high degree of protection at the specified beam quality, but underperform at others’.(2) Furthermore, in a follow-up study, Pasciak et al.(3) defined and used scatter mimicking primary beams for protective apron assessment. The reader is left to wonder, would the Sample 4 material still be 0.36 mm Pb equivalent using a scatter mimicking primary beam, or scattered radiation. With only a 2% weight savings, the assessment procedure is relevant to assure the claim of superiority holds true.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".