Improving quality assurance for assembled COMS eye plaques using a pinhole gamma camera
Bibliographic record
Abstract
A quality assurance system has been designed to verify the location and strength of seeds loaded in a brachytherapy eye plaque. This system consists of (1) a pinhole camera in conjunction with a Lumisys ACR-2000i computed radiography (CR) unit to image the location and measure the relative strength of the seeds with autoradiography, and (2) a source strength jig with a survey meter to estimate the total activity of the seeds in the plaque. Five holders of different sizes were made for fixation of the COMS (Collaborative Ocular Melanoma Study) plaques (12, 14, 16, 18, and 20 mm) in the camera. The plaque-to-pinhole distance (dpp) has been optimized to be 30 mm to give approximately uniform intensity on the CR image for uniformly loaded COMS plaques. The pinhole-to-detector distance (dpd) can be kept at either 30 mm for 1:1 scale, or at larger distances for higher magnification. For a 1:1 scaling and pinhole diameter of 0.345 mm, useful images are obtained with time-activity product (mCi sec) ranging from 5 to 250 mCi sec. Within this range, the pinhole system is able to differentiate seed activities of >10%. The resulting pinhole autoradiograph is able to (1) confirm the correct number of seeds loaded in the plaque, (2) verify the proper sitting of the seeds in the silastic carrier and the plaque, (3) verify the relative activity distribution of the seeds loaded in the plaque, and (4) potentially evaluate the integrity of the seed. The source strength measurement system is able to measure the total strength of seeds in the plaque ranging from 10 to 80 mCi with an uncertainty of 5%.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".