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Record W2132092961 · doi:10.1109/tns.2008.2005980

New X-Ray Detectors for Exotic Atom Research

2009· article· en· W2132092961 on OpenAlexaff
J. Márton, M. Cargnelli, T. Ishiwatari, P. Kienle, K. Nikolics, E. Widmann, J. Zmeskal, M. Bazzi, M. Catitti, C. Curceanu, C. Guaraldo, M. Iliescu, P. Levi Sandri, V. Lucherini, S. Okada, D. Pietreanu, A. Romero Vidal, A. Scordo, D. Sirghi, F. Sirghi, Oton Doce, G. Beer, L. Bombelli, C. Fiorini, T. Frizzi, A. Longoni, A.M. Bragadireanu, T. Ponta, F. Ghio, B. Girolami, R. Hayano, H. Tatsuno, S. Xe-Hi, M. Iwasaki, P. Lechner, H. Soltau, L. Strüder

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPhysicsDetectorHadronNuclear physicsSilicon drift detectorMuonSpectrometerDeuteriumExotic atomAtomic physicsOptics

Abstract

fetched live from OpenAlex

Hadronic atoms being Coulomb-bound systems in which the electron is substituted by a hadron like a negatively charged K meson are perfect probes for the study of strong interaction at lowest energies using x-ray spectroscopy. New large area x-ray detectors (silicon drift detectors, SDDs) were developed to provide excellent energy resolution as well as timing capability. For the first time large area SDDs were employed to measure the L-lines of kaonic helium at high precision thus succeeding in clarifying a puzzle persisting for 30 years since the 70's. An array of about 200 even more sophisticated SDDs (1 cm2SDDs with monolithically integrated FET) will be used to perform precision measurements (i.e., at the eV level) of kaonic hydrogen and kaonic deuterium at the DAFNE Phi factory of LNF/Italy. The new x-ray detectors and their performance for precision experiments in the accelerator environment are presented.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.003

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 head0.057
GPT teacher head0.318
Teacher spread0.261 · 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 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

Citations7
Published2009
Admission routes1
Has abstractyes

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