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Record W4206644916 · doi:10.1016/j.nima.2021.166248

First gadolinium loading to Super-Kamiokande

2022· article· en· W4206644916 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

VenueDigital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) · 2022
Typearticle
Languageen
FieldEngineering
TopicSuperconducting Materials and Applications
Canadian institutionsUniversity of British ColumbiaBritish Columbia Institute of Technology
Fundersnot available
KeywordsGadoliniumSuper-KamiokandeEnvironmental scienceMaterials sciencePhysicsNuclear physicsMetallurgy

Abstract

fetched live from OpenAlex

In order to improve Super-Kamiokande’s neutron detection efficiency and to thereby increase its sensitivity to the diffuse supernova neutrino background flux, 13 tons of (gadolinium sulfate octahydrate) was dissolved into the detector’s otherwise ultrapure water from July 14 to August 17, 2020, marking the start of the SK-Gd phase of operations. During the loading, water was continuously recirculated at a rate of 60 m/h, extracting water from the top of the detector and mixing it with concentrated solution to create a 0.02% solution of the Gd compound before injecting it into the bottom of the detector. A clear boundary between the Gd-loaded and pure water was maintained through the loading, enabling monitoring of the loading itself and the spatial uniformity of the Gd concentration over the 35 days it took to reach the top of the detector. During the subsequent commissioning the recirculation rate was increased to 120 m/h, resulting in a constant and uniform distribution of Gd throughout the detector and water transparency equivalent to that of previous pure-water operation periods. Using an Am–Be neutron calibration source the mean neutron capture time was measured to be , which corresponds to a Gd concentration of ppm, as expected for this level of Gd loading. This paper describes changes made to the water circulation system for this detector upgrade, the Gd loading procedure, detector commissioning, and the first neutron calibration measurements in SK-Gd.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0020.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.201
Teacher spread0.188 · 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