Sci-Sat AM(2): Brachy - 04: Brachytherapy Air-Kerma Calibrations at Ionizing Radiation Standards, NRC
Bibliographic record
Abstract
The majority of Canadian cancer clinics now offer brachytherapy treatments, but source calibrations currently require transfer chambers to be sent out of the country. The logistical difficulties involved in shipping delicate and crucial medical equipment internationally prompted the Canadian user committee to encourage the Ionizing Radiation Standards (IRS) group, Institute for National Measurement Standards, NRC, to develop brachytherapy standards in Canada and to provide brachytherapy calibrations to the Canadian radiation therapy community. The IRS group has undertaken the development of primary standards for brachytherapy. Using a technique similar to that employed by the French primary standards Laboratoire National Henri Becquerel (LNHB), the IRS version of the dosimetric standard realization for 192Ir will use a non-contact, indirect distance measuring method. The HDR calibration facility is under construction and should be operational in 2010. If there are no unexpected set-backs, HDR calibrations should be available in the beginning of 2011. In addition, IRS is actively searching for a Ph.D. candidate to begin development of an IRS LDR facility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.229 | 0.065 |
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".