Production of Medically Important Radionuclides <sup>52</sup>Mn and <sup>90</sup>Nb
Bibliographic record
Abstract
Over the final reporting period of this project, we at MGH finalized our effort on Project 2: Production and Characterization of 90Nb which, as per our previous report led us to an interesting application of mass spectrometry in radiometal chemistry. Overall, our research has developed parameters and procedures for delivering high 90Nb for preclinical and translational applications by initializing the cyclotron targetry and separation chemistry for delivering 90Nb in a chemical form suitable for subsequent development of 90Nb-based PET radiotracers, and most recently we have published on the mass spectrometry applications described in the present report. We have been working with MSKCC (PI Jason Lewis) on the 90Nb methodology and have had input from UAB (PI Suzy Lapi). An in-person meeting was held during the upcoming funding period with 2 PIs who are co-organizing the Radiochemistry Symposium (Lapi and Vasdev) and Program Director Dr. Ethan Balkin, during the ACS National Meeting in March 2018, and 2 PIs (Lewis and Vasdev) co presented in at the World Federation of Nuclear Medicine and Biology at a symposium sponsored by the Australian Nuclear Sciences and Technology Organisation, where they are both collaborating, in Melbourne, Australia in April 2018. Future projects and collaborations are under discussion with the Lapi lab to focus on new applications of 76Br chemistry, and a new collaboration has already resulted with the Lewis lab on 18F radiochemistry that employ iodonium ylide based precursors developed in the Vasdev lab, for clinical production of [18F]MFBG. It is noteworthy that the PI has now relocated to the University of Toronto and has 2 cyclotrons (IBA Cyclone and Scanditronix MC-17) that will also be used to explore new 11C-radiochemistry including [11C]CO.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.011 |
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".