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Record W2907100835 · doi:10.1109/icsens.2018.8589653

A Novel Plastic Optical Fibre-Based Scintillator Detector's Response in Neutron Irradiation up to 400 MeV

2018· article· en· W2907100835 on OpenAlexaff
Crystal Penner, Cheryl Duzenli, Sinéad O’Keeffe, Boris Stoeber, Cornelia Hoehr

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsTRIUMFSpinal Cord Injury BCUniversity of British Columbia
Fundersnot available
KeywordsScintillatorNeutron detectionMaterials scienceNeutronTerbiumIrradiationNeutron radiationDetectorBeam (structure)OpticsDosimeterNeutron temperatureRadiochemistryOptoelectronicsNuclear physicsPhysicsRadiationChemistryLuminescence

Abstract

fetched live from OpenAlex

A study was carried out to determine if a novel, millimeter sized Terbium-activated Gadolinium Oxysulfide optical fibre detector can detect neutrons from a 0×400 MeV neutron beam. Two different sensor samples with different distributions of scintillator powder were tested. Both responded to the neutron irradiation. The denser sample was then explored to measure the vertical profile of the neutron beam. This demonstrates that the sensor can be used to detect neutrons.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.258
Teacher spread0.244 · 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.

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

Citations2
Published2018
Admission routes1
Has abstractyes

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