Bibliographic record
Abstract
A process for manufacturing targets for technetium-99m production, via 100 Mo(p, 2n) 99m Tc, is presented.Targets consist of a thin layer of molybdenum-100 pressed into a copper heat sink complete with water cooling channels and O-rings.These targets are designed to be irradiated in cyclotrons at hospitals and regional pharmacies around the world to replace fission produced 99 Mo.The iterations and tests leading to the final target design and processing procedures are presented.Physical descriptions of the targets are given, followed by the procedure for manufacture, and process improvements for large-scale production.The importance of 99m Tc as a diagnostic imaging tool is presented, with references to instability of current sources and recent shortages, which have had led to world-wide efforts to develop non-reactor produced isotopes.requirements.Meetings with Glenn and his students are enjoyable.Scott Langille, Curtis St. Louis, and Paul Keeping played a pivotal role in the production of targets.They gave novel ideas, helping hands, and humour from the beginning of the project, right until the end.The Science Technology Centre, specifically, I would like to thank Graham Beard, Ron Roy, and Steve Tremblay.Not only is the level of their work top notch, they also had insight when developing new parts and accommodated
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".