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Record W3039230910 · doi:10.3390/app10134610

Fiber-Optic Bragg Gratings for Temperature and Pressure Measurements in Isotope Production Targets for Nuclear Medicine

2020· article· en· W3039230910 on OpenAlexafffund
Michael Bakaic, Matthew Hanna, Cyril Hnatovsky, Dan Grobnic, Stephen J. Mihailov, S. Stefan Zeisler, Cornelia Hoehr

Bibliographic record

VenueApplied Sciences · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsNational Research Council CanadaTRIUMF
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFiber Bragg gratingMaterials scienceOpticsNeutronOptical fiberBragg peakTemperature measurementBeam (structure)Fiber optic sensorOptoelectronicsNuclear physicsPhysicsWavelength

Abstract

fetched live from OpenAlex

A Bragg grating inscribed into an inorganic optical fiber was tested in proton and neutron fields up to doses of 472 Gy. Observation showed that radiation had no effect on the performance of the Fiber Bragg Grating (FBG) used as a gauge measuring temperature and pressure. The FBG sensor was subsequently employed to measure the temperature and pressure inside a liquid isotope production target for nuclear medicine. The fiber Bragg grating measured the temperature and pressure of a water target as a 12 MeV proton beam impinged on it in real time and was tested with beam currents of up to 20 µA.

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 score0.575
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

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

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 head0.029
GPT teacher head0.241
Teacher spread0.212 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

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