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Record W1603667236 · doi:10.48550/arxiv.1503.08541

Hybrid ECAL: Optimization and Related Developments

2015· preprint· en· W1603667236 on OpenAlexaff
Taikan Suehara, H. Hirai, Hiroki Sumida, H. Ueno, Y. Sudo, T. Yoshioka, K. Kawagoe

Bibliographic record

VenuearXiv (Cornell University) · 2015
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsInstitute of Particle Physics
FundersDeutsches Elektronen-SynchrotronMinistry of Education, Culture, Sports, Science and TechnologyJapan Society for the Promotion of ScienceCERN
KeywordsCalorimeter (particle physics)GranularityDetectorPhysicsScintillatorColliderNuclear physicsInternational Linear ColliderParticle physicsElectronic engineeringElectrical engineeringComputer scienceEngineeringOperating system

Abstract

fetched live from OpenAlex

Hybrid ECAL is a cost-conscious option of electromagnetic calorimeter (ECAL) for particle flow calorimetry to be used in a detector of International Linear Collider (ILC). It is a combination of silicon-tungsten ECAL, which realizes high granularity and robust measurement of electromagnetic shower, and scintillator-tungsten ECAL, which gives affordable cost with similar performance to silicon. Optimization and a data acquisition trial in a test bench for the hybrid ECAL are described in this article.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.042
GPT teacher head0.191
Teacher spread0.148 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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