Trigger performance of plastic scintillator detectors with silicon photomultiplier readout for cosmic ray muons
Bibliographic record
Abstract
Abstract A plastic scintillating fiber (SciFi) detector with multi-channel readout electronics based on the Citiroc1A chip is being developed for muon tomography application. In this study, to provide external triggers of cosmic ray muons to the SciFi detector, we fabricated two 10 cm × 10 cm × 2 cm plastic scintillators with wavelength shifting fibers (WLS) and evaluated their trigger performance with silicon photomultiplier readout. The results showed that the plastic scintillators embedded with WLS fibers obtained a light collection increase of up to three times in comparison to those without WLS fibers, and exhibited good discrimination of cosmic ray muons from ambient gamma rays. The trigger system consisted of the two scintillator detectors could achieve a high trigger efficiency up to 99% within a coincidence time window of 10 ns. Its inherent latency of both trigger strategy and readout electronics was well below 30 ns, making it feasible to offer external triggers to Citiroc1A with a peaking time tunable from 12.5 ns to 87.5 ns.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".