Conceptual Design of TR¹⁰⁰⁺: An Innovative Superconducting Cyclotron for Commercial Isotopes Production
Bibliographic record
Abstract
Utilizing dedicated cyclotrons to produce medical isotopes is an arising technology in hospitals across Canada. Thus, in January 2015, the CycloMed99 team, led by TRIUMF, demonstrated a breakthrough in producing the world’s most highly used medical isotope, technetium-99m (Tc-99m), on existing medical cyclotrons. Now we propose to design an innovative superconducting cyclotron for production of commercially valuable radioisotopes. This project will be focusing on a proton energy of 70-150 MeV and proton current of 2 mA. In this energy range, numerous increasingly demanded radionuclides can be produced, either as parent nuclei for generator use, or directly as a active pharmaceutical ingredient, e.g. Strontium-82 (Sr-82), Actinium-235 (Ac-235) and Bismuth-213 (Bi-213). Our machine shall be designed to accelerate H²⁺, by injection from external ion source and extraction by stripping. This shall allow to simultaneously extract multiple cw proton beams of variable currents and potentially variable energies to multiple experimental stations with extremely high extraction efficiency. The basic parameters of the machine and the simulations of stripping extraction will be presented.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".