Real-Time Coincidence Detection System for Digital High Resolution APD-based Animal PET Scanner
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A centralized, fully digital, FPGA-based coincidence detection system has been developed for the LabPET APD-based scanner. The digital flexibility allows excellent timing resolution using digital signal processing and high precision crystal identification. In this digital architecture, fast AND-gate coincidence detection is no longer possible due to signal analysis delay. Timestamp based coincidences must be carried out by a central digital process that handles huge amounts of data. A 45 MHz system clock is used by free running ADCs and reference time counters. Event timestamp is refined to ~0.7 ns resolution with digital analysis. A real-time digital coincidence detection system capable of processing 32 million single events per second is proposed to support a fully digital APD-based architecture. The coincidence engine retains a technology independent structure, making it easily reusable in subsequent generation architectures. The system detects prompt coincidences and evaluates random coincidences using both a delayed-window coincidence and the singles count rate. Finally, it supports dynamic adaptive coincidence windowing for multi-crystal PET scanners, ranging from 0 to 100 ns in 0.7 ns increments
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it