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Record W4407363550 · doi:10.1063/5.0250148

Current status and perspectives of the ACCESS project

2025· article· en· W4407363550 on OpenAlexaff
D. Helis, P. Carniti, E. Celi, D. Chiesa, Jacqueline Corbett, I. Dafinei, P. C. F. Di Stefano, F. Ferella, Zbigniew Galazka, S. Ghislandi, C. Gotti, R. Knöbel, J. Kotila, J. Kostensalo, S.S. Nagorny, S. Nisi, L. Pagnanini, G. Pessina, S. Pirro, S. Pozzi, A. Puiu, S. Quitadamo, J. Suhonen, Yanchang Zhu

Bibliographic record

VenueAIP conference proceedings · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsQueen's University
FundersEuropean Commission
KeywordsCurrent (fluid)Computer scienceElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

The ACCESS project (Array of Cryogenic Calorimeters to Evaluate Spectral Shapes) aims to establish a novel technique to perform precision measurements of forbidden beta-decays, whose spectral shape is a crucial benchmark for Nuclear Physics calculations and plays a pivotal role in Astroparticle Physics experiments. ACCESS will operate a pilot array of four tellurium dioxide crystals as cryogenic calorimeters at 10 mK. Three of them will be doped with different beta emitters (99Tc, 151Sm, 210Pb/210Bi), while the last natural one will be used for effective background subtraction. In the intermediate steps of the project also natural crystals such as cadmium tungstate (CdWO4) and indium dioxide (In2O3) will be used to investigate the beta decay of 113Cd and 115In respectively. In this work, we will describe the ACCESS project, summarizing the current status and future perspectives. Moreover, we will discuss the preliminary results obtained with indium-based crystals operated as cryogenic calorimeters.

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)0.023
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0100.010
Open science0.0040.005
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0320.013

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 head0.037
GPT teacher head0.309
Teacher spread0.272 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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