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Record W4387516975 · doi:10.1093/rpd/ncad013

A comprehensive Monte Carlo simulation of the neutron response of multi-element microdosimetric detectors based on THick Gas Electron Multiplier

2023· article· en· W4387516975 on OpenAlexafffund
Ranbir Singh, Soo Hyun Byun

Bibliographic record

VenueRadiation Protection Dosimetry · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsMcMaster University
FundersCANDU Owners Group
KeywordsMonte Carlo methodGas electron multiplierPhysicsKermaFluenceDetectorNeutronElectronNuclear physicsMaterials scienceIrradiationOpticsNuclear medicineDosimetry

Abstract

fetched live from OpenAlex

We present comprehensive Monte Carlo simulations for the neutron response of the multi-element microdosimetric detector based on THick Gas Electron Multiplier (THGEM). Simulations were carried out using the MCNP6.2 code to calculate the deposited energy spectrum in the gaseous sensitive volumes for three different configurations, 7 × 3, 19 × 5, 37 × 7 that occupy a cylindrical volume of 5-cm diameter by 5-cm length. The energy response was computed from 10 keV to 2 MeV. The response variation was investigated between sensitive volumes as well as between layers. The simulated energy response showed a good agreement against the evaluated fluence-to-kerma conversion coefficients in the energy region 10-100 keV, whereas discrepancies were observed in the region above 250 keV. The angular response simulations showed a variation of less than 10%.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
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 head0.021
GPT teacher head0.272
Teacher spread0.251 · 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 designSimulation or modeling
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
Published2023
Admission routes2
Has abstractyes

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