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Record W2567357652

The Development Of A Gadolinium Isopropoxide-Loaded Plastic Scintillator As An Active Neutron Veto For The SuperCDMS SNOLAB Experiment

2016· article· en· W2567357652 on OpenAlexaboutno aff
David-Michael T Poehlmann

Bibliographic record

VenueUniversity of Minnesota Digital Conservancy (University of Minnesota) · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsnot available
FundersUniversity of Minnesota
KeywordsGadoliniumScintillatorVetoNeutronMaterials scienceNuclear physicsRadiochemistryNuclear engineeringPhysicsChemistryOpticsEngineeringMetallurgyPolitical scienceLawDetector
DOInot available

Abstract

fetched live from OpenAlex

The Cryogenic Dark Matter Search (CDMS) is an experiment that looks for dark matter, specifically weakly-interacting massive particles (WIMPs).Currently, the SuperCDMS SNOLAB dark matter detector, the successor to SuperCDMS Soudan, is being developed for placement at the SNOLAB research facility in Canada.[1] As the sensitivity of this detector is increased, the suppression of neutron backgrounds through the traditional methods of using highly radiopure materials and passive shielding becomes much more difficult.[2] Single scatter neutron events can produce nuclear recoils that are indistinguishable from WIMP interactions.One method of measuring the background radiation is by replacing some of the passive shielding with an active neutron veto composed of a metal-loaded plastic scintillator.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.211
Teacher spread0.196 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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