Development of medicine-intended isotope production technologies at Yerevan Physics Institute
Bibliographic record
Abstract
Accelerator-based 99mTc and 123I isotopes production technologies were created and developed at A.Alikhanyan National Science Laboratory (former Yerevan Physics Institute - YerPhI). The method involves the irradiation of natural molybdenum (for 99mTc production) and natural xenon (for 123I production) using high-intensity bremsstrahlung photons from the electron beam of the LUE50 linear electron accelerator located at the YerPhI. We have developed and tested the extraction of 99mTc and 123I from the irradiated natural MoO3 and natural Xe, respectively. The production method has been developed and shown to be successful. The current activity is devoted to creation and development of the technology of direct production 99mTc on the 100Mo as target materials using the proton beam from an IBA C18/18 cyclotron. The proton cyclotron C18/18 (producer – IBA, Belgium) was purchased and will be installed nearby AANL (YerPhI) till end 2014. The 18 MeV protons will be used to investigate accelerator-based schemes for the direct production of 99mTc. Main topics of studies will include experimental measurement of 99mTc production yield for different energies of protons, irradiation times, intensities, development of new methods of 99mTc extraction from irradiated materials, development of target preparation technology, development of target material recovery methods for multiple use and others.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".