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Calibration of Solid State Nuclear Track Detectors for rare event searches

2025· article· en· W4408406436 on OpenAlexafffund
M. Kalliokoski, G. Lévi, A. Maulik, I. Ostrovskiy, L. Patrizii, J. L. Pinfold, Z. Sahnoun, G. Sirri, R. Soluk, Michael Staelens, V. Togo, A. Upreti

Bibliographic record

VenueJournal of Instrumentation · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsUniversity of Alberta
FundersNational Synchrotron Radiation LaboratoryCERNUniversity of AlbertaNational Science Foundation
KeywordsCalibrationNuclear trackSolid-stateTrack (disk drive)DetectorEvent (particle physics)Nuclear physicsNuclear engineeringState (computer science)PhysicsComputer scienceEnvironmental scienceOpticsAlgorithmEngineering physicsEngineeringAstrophysics

Abstract

fetched live from OpenAlex

Abstract The calibration of the CR39 ® and Makrofol ® Nuclear Track Detectors of the MoEDAL experiment at the CERN-LHC was performed by exposing stacks of detector foils to heavy ion beams with energies ranging from 340 MeV/nucleon to 150 GeV/nucleon. After chemical etching, the base areas and lengths of etch-pit cones were measured using automatic and manual optical microscopes. The response of the detectors as measured by the ratio of the track-etching rate over the bulk-etching rate, was determined over a range extending from their threshold at Z/ β ∼ 7 and ∼ 50 for CR39 and Makrofol, respectively, up to Z/ β ∼ 92.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.190

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 head0.012
GPT teacher head0.279
Teacher spread0.267 · 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 designOther design
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

Citations1
Published2025
Admission routes2
Has abstractyes

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