MATHEMATICAL MODELS OF THE EMBRYO AND FETUS FOR USE IN RADIOLOGICAL PROTECTION
Bibliographic record
Abstract
This development of new mathematical models arose from our current work in external neutron dosimetry for the embryo and fetus when pregnant women travel at commercial aircraft altitudes. A problem of concern in radiation protection is exposure of pregnant women to ionizing radiation because of the high radiosensitivity of the embryo and fetus. Special regulations and dosimetric considerations are necessary for pregnant women at the work place and in the public. To perform dosimetry, mathematical models for the embryo and the fetus, together with the modified adult female model for pregnant woman, are required. There are no models available for embryo. Models developed for the fetus need to be updated with the new reference values such as those in ICRP Publication 89. This article presents mathematical models for the embryo and fetus at different stages: the embryo at 8 wk and the fetus at the end of each trimester. In addition to fetal skeleton, the fetal brain is explicitly modeled because of its high radiosensitivity. All model parameters are determined from the most recent reference values available. The models are designed so that an interpolation can be easily performed to generate a model of embryo/fetus at any given stage of development. This feature also allows convenient adaptation of the models to different reference values representing various ethnic populations. The new mathematical models presented here were developed for external dosimetry. They can also be used for internal dosimetry purposes, if other organs inside the female phantom are adjusted accordingly.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".