Dose measurements near a non-radioactive gold seed using radiographic film
Bibliographic record
Abstract
The dose distribution near a non-radioactive gold seed under a 6 MV photon beam was measured using radiographic film, water equivalent bolus and solid water slabs. This type of small seed is typically used as a marker in target positional verification using a portal imager for conformal prostate treatment such as intensity modulated radiation therapy. A stack of three films was placed on top of the seed located on a soft bolus. Solid water slabs were then placed on top of the film. The films were exposed using a small 1x1 cm2 field. Then, using a similar experimental set-up and exposure, another stack of three films was placed under the seed, which was then covered by the soft bolus and solid water slabs. The cross-plane axial beam profiles at different depths, depending on the thickness of the film package, were measured. From the group of beam profiles above and below the seed, the dose distribution along a selected vertical line within the profiles was easily plotted. Compared to the dose with no seed at the isocentre and 5 cm of solid water, there was about a 21% increase in dose at 0.35 mm above the seed. On the other hand, there was about a 22% decrease in dose at the same distance below the seed. The dosimetry of the calibrated film was verified with a MOSFET detector. The change in dose due to the seed by varying the incident beam angles was also measured for this note.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".