The Dose Spiking Technique for Measuring Low Doses in Deciduous Teeth Enamel Using EPR Spectroscopy for Retrospective and Accident Dosimetry
Bibliographic record
Abstract
ABSTRACT: Dose estimation by electron paramagnetic resonance (EPR) has been accomplished using the standard EPR dosimetry technique (ISO protocol 13304-1 for EPR retrospective dosimetry). However, different studies showed that these techniques have high measurement errors in measuring the low doses (10-100 mGy) in enamel. This work proposes a new method to make a dosimetric signal visible and measurable at low doses. The sample was purified using both chemical and mechanical processes. The pure sample mass and position and the EPR acquisition parameters were optimized to enhance the spectrometer's sensitivity for the quantitative low dose measurements. At the same time to reduce errors from the sample and spectrum anisotropy, the total doses (low plus spike) and the spike dose (4 Gy) were measured by rotating 0 to 360 degrees (i.e., 40 degrees at a time) relative to constant magnetic field direction using a goniometer. Subsequently, the spectra were averaged after their g-factor normalization. However, at low doses (<30 mGy), the radiation induced signal (RIS) was obscured by the background signal (BGS). So, the dose spiking technique was used as an alternative method. Ten low-dose deciduous molar tooth enamel (10-100 mGy) samples were spiked to the higher doses by delivering 4 Gy and measured using the X-band continuous wave (CW) EPR (Bruker EMXmicro) spectrometer. The total dose EPR signal was distinctly visible, and the peak-to-peak (P2P) amplitude height was measured. Then, the total dose was subtracted with the spike, often called a reference sample, to determine the initial low doses. The measurement errors using this method were lower than the previous methods. These results demonstrated that this method could be promising for solving low dose measurement problems in EPR dosimetry with deciduous and permanent tooth enamel.
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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 | 0.000 | 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 | 0.001 |
| 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".