Production, separation and evaluation of Tc99m and Mo99 from accelerator transmutation of Mo100
Bibliographic record
Abstract
1439 Objectives To demonstrate potential for translation to clinic of Tc99m and molybdenum-99 (Mo99) produced from linear accelerator-transmutated Mo100 Methods 1-mm natural molybdenum metal (9.63% abundance Mo100, Sigma) was irradiated in a stack of 20 1.25-cm discs at 20 MeV/10 kW. Tests to determine the most efficient dissolution solvent(s) for metal target and conversion to Na2MoO4 were performed. Acid mixtures studied were 50%w/v HNO3 (1), 50%v/v HNO3 (2), HNO3:H2SO4:H2O (5:3:2) (3), with or without heat. We possess solvent extraction generator technology previously in clinical use for fission-produced Mo99, and validated for low specific activity Mo99 from Mo98(n,γ)Mo99. Results Mo99 yields were 1.7GBq and 4.6GBq. Optimization runs using 1-mm, 2.4cm diameter discs are in progress, with a focus on improved beam targets. Distribution of activity over individual discs (Fig 1A) correlated very closely to MCNP modeling, with disc10 at 54.2% and disc20 at 26.0% of activity of disc1 (versus 54.7, 29.4% for modeling). Nb95 and Nb96 impurities were seen (Fig 1B), presumably from Mo-96(γ,p)Nb-95 and Mo-97(γ,p)Nb-96 reactions. Efficiency of dissolution was 3>2>1, with complete dissolution by 3 obtained for a tranche of 12 discs ( Conclusions Production chain shows good potential for clinical translation. Use of Mo99 isotopically-enriched targets should increase irradiation yields ten-fold and minimize radionuclidic impurities. Research Support Health Sciences Centre Foundatio
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".