Poster — Wed Eve—15: Development of Multiple Coincidence Compton Imager
Bibliographic record
Abstract
We report on the development of a new type of nuclear medicine imaging device — a Multiple Coincidence Compton Imager (MCCI). MCCI is based on the principle of electronic collimation and is expected to provide comparable resolution and better sensitivity than currently available SPECT systems. Furthermore, MCCI is using the simultaneous acquisition of several photons from a cascade allowing improved localization of the origin of any single radioactive disintegration. We have developed data simulation software and a simplified image reconstruction algorithm, that can be used to make predictions about the sensitivity and the reconstructed image spatial resolution that will be achieved by the MCCI system. In particular, our simulations of a small animal systems, using Silicon and CZT detector combination confirmed that the Compton camera is able to provide 10 to 100 times higher sensitivity than a typical SPECT system and image resolution around 1 mm FWHM for small animal studies.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".