Potential Ways to Address Shortage Situations of <sup>99</sup>Mo/<sup>99m</sup>Tc
Why this work is in the frame
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Bibliographic record
Abstract
<sup>99m</sup>Tc, the most common radioisotope used in nuclear medicine, is produced in a nuclear reactor from the decay of <sup>99</sup>Mo. There are only a few aging nuclear reactors around the world that produce <sup>99</sup>Mo, and one of the major contributors, the National Research Universal (Canada), ceased production on October 31, 2016. The National Research Universal produced approximately 40% of the world’s <sup>99</sup>Mo supply, so with its shut down, shortages of <sup>99</sup>Mo/<sup>99m</sup>Tc are expected. <b>Methods:</b> Nuclear pharmacies and nuclear medicine departments throughout the United States were contacted and asked to provide their strategies for coping with a shortage of <sup>99</sup>Mo/<sup>99m</sup>Tc. Each of these strategies was evaluated on the basis of its effectiveness for conserving <sup>99m</sup>Tc while still meeting the needs of the patients. <b>Results:</b> From the responses, the following 6 categories of strategies, in order of importance, were compiled: contractual agreements with commercial nuclear pharmacies, alternative imaging protocols, changes in imaging schedules, software use, generator management, and reduction of ordered doses or elimination of backup doses. <b>Conclusion:</b> The supply chain of <sup>99</sup>Mo/<sup>99m</sup>Tc is quite fragile; therefore, being aware of the most appropriate coping strategies is crucial. It is essential to build a strong collaboration between the nuclear pharmacy and nuclear medicine department during a shortage situation. With both nuclear medicine departments and nuclear pharmacies implementing viable strategies, such as the ones proposed, the amount of <sup>99m</sup>Tc available during a shortage situation can be maximized.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it