Study of light collection in multi-crystal detectors
Bibliographic record
Abstract
Phoswich detectors are currently being considered by a number of investigators for depth-of-interaction measurement in PET and multi-modality emission/transmission imaging. Many parameters affect light collection and S/N ratio from such detectors made of crystals having different emission wavelength, refractive index and light output. In this work, the effects of crystal intrinsic and extrinsic properties on light propagation and light collection efficiency were studied. Avalanche photodiode (APD) and photomultiplier tube (PMT) readouts were used to study the light output at different wavelengths. Experiments and simulations with DETECT97 have shown that light collection efficiency and energy resolution degrade steadily with distance from photodetector, mainly as a result of additional crystal interfaces. Simulations indicate that ground surfaces and high reflectivity diffuse reflectors maximise light output, but measurements tend to show that similar results are obtained with polished surfaces due to the presence of crystal defects. An excitation band at 400 nm in GSO is found to absorb a fraction of the light from LSO. This effect is more significant with the PMT photodetector, which has its maximum sensitivity in the 400-nm range. Inconsistent results observed for LSO and YSO are shown to be compatible with the presence of light scattering within these crystals.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".