Quantification of low dose signal in EPR tooth dosimetry - a novel approach
Bibliographic record
Abstract
For radiation exposures below 100 mGy, the dosimetric signal in tooth enamel is too small to be measured by using the traditional dose reconstruction procedure. This is because low amplitude zero-added-dose signal can not be identified in an EPR spectrometer. A technique is presented wherein, zero-added-dose signal. when amplified by a proper known dose, can be measured in the EPR spectrometer. Mathematically, the accidental dose x is modified by a known amount of exposure, y (large enough so that the signal is now visible), and total exposure becomes x' = x + y, which is the modified-zero-added dose. The exposure x' is then quantified using the conventional backward extrapolation method and the accidental dose can be measured. In a laboratory controlled experiment, the feasibility of dose reconstruction in the 100 mGy range has been demonstrated. This may enable measurements of dose even due to suspected low exposure in 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".