Development and performance evaluation of ECal modules in China for the NICA-MPD
Bibliographic record
Abstract
The Electromagnetic Calorimeter (ECal), a critical sub-detector of Multi-Purpose Detector (MPD) at Nuclotron-based Ion Collider fAcility (NICA), is designed to identify and measure electrons, photons and neutral mesons produced in high-energy heavy-ion collisions. Its Shashlyk-type architecture combines lead absorbers and plastic scintillators in a layered geometry to optimize measurement precision. 768 ECal modules (one-third of the whole ECal) have been developed by the Chinese MPD group. The mass production process and a specially designed performance test system for quality assurance are described here. The result from cosmic ray tests demonstrates uniformity among the produced modules, confirming that the mass-produced ECal modules met the design specifications and that the quality control procedures implemented during mass production are effective. Furthermore, this paper focuses on the physical feasibility, conducting research on neutral mesons reconstruction using the ECal based on [Formula: see text] collisions at [Formula: see text] [Formula: see text]GeV simulated with realistic event generator.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".