Understanding radionuclide production in gas target systems: the effect of adsorption on the target body
Bibliographic record
Abstract
Gas target systems have been used for decades on cyclotrons to produce radionuclides for medical imaging. However, the activity recovered from such targets is often lower than its theoretically predicted value. Past research has suggested that nuclide interactions with the walls of the target body may play a key role in the loss of recoverable radionuclide activity. Here, we consider gas targets and modify the standard radionuclide production equation by adding a loss term representing radionuclides depositing on the walls of the target. We derive the form of the deposition term based on a simple adsorption model which is then linearized by solving for leading order terms. The resulting production equation uses one fitting parameter to give an estimate of the recoverable activity produced in a target system, taking adsorption into account. The model is then fit to six data series, taken in-house and reported in the literature and a parity plot compares model predictions to experimental data. The model is able to better track the data than any previous models, and points towards a phenomenological understanding of adsorption in target systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".