MétaCan
Menu
Back to cohort
Record W4407778010 · doi:10.3103/s0027134924700747

Fabrications and Performance Test of ECal Modules in China for NICA-MPD Experiment

2024· article· en· W4407778010 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMoscow University Physics Bulletin · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsTest (biology)ChinaPhysicsComputer scienceNuclear physicsPolitical scienceGeologyLaw

Abstract

fetched live from OpenAlex

Electromagnetic Calorimeter (ECal), a subdetector of Multipurpose Detector (MPD), is designed to identify electrons, photons, and neutral hadrons produced in high-energy heavy-ion collisions at nuclotron-based ion collider facility (NICA) and measure their energies and positions. A Shashlyk-type sampling calorimeter composed of lead plates as absorbers and plastic scintillators arranged alternately was selected for ECal. Chinese MPD consortium is responsible for the development of 768 ECal modules which is $$1/3$$ of the whole ECal detector. In this report, the mass production process of ECal modules and a performance test system designed for the mass production will be presented. The uniformity of the ECal modules achieved based on cosmic ray test will be discussed. Preliminary results demonstrate the produced ECal modules met the design requirements, indicating the quality control in mass production is effective. These modules were delivered to the Joint Institute for Nuclear Research (JINR) at Dubna in March 2023, and will soon be installed on MPD detector for further commissioning.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.209
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it