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Record W3100828499

The calibration system for the photomultiplier array of the SNO+ experiment

2015· article· en· W3100828499 on OpenAlexaff
Rui Alves, S. Andringa, Stella Bradbury, J. Carvalho, D. Chauhan, K. Clark, I. T. Coulter, F. Descamps, L. Gurriana, C. Kraus, J. Maneira, J. Rose, L. F. Oleiro Seabra, P. Skensved, J. Waterfield

Bibliographic record

VenueRepositório Comum (Repositório Científico de Acesso Aberto de Portugal) · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsQueen's UniversityLaurentian University
Fundersnot available
KeywordsPhotomultiplierCalibrationDetectorOpticsFabricationOptoelectronicsSilicon photomultiplierMonte Carlo methodLight-emitting diodeMaterials sciencePhysicsScintillator
DOInot available

Abstract

fetched live from OpenAlex

A light injection system using LEDs and optical fibres was designed for the calibration and monitoring of the photomultiplier array of the SNO+ experiment at SNOLAB. Large volume, non-segmented, low-background detectors for rare event physics, such as the multi-purpose SNO+ experiment, need a calibration system that allow an accurate and regular measurement of the performance parameters of their photomultiplier arrays, while minimising the risk of radioactivity ingress. The design implemented for SNO+ uses a set of optical fibres to inject light pulses from external LEDs into the detector. The design, fabrication and installation of this light injection system, as well as the first commissioning tests, are described in this paper. Monte Carlo simulations were compared with the commissioning test results, confirming that the system meets the performance requirements.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.023
GPT teacher head0.282
Teacher spread0.259 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations13
Published2015
Admission routes1
Has abstractyes

Explore more

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