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Record W2021363066 · doi:10.1142/s0217751x0904347x

KAONIC ATOMS AT DAΦNE — THE SIDDHARTA EXPERIMENT

2009· article· en· W2021363066 on OpenAlexaff
J. Zmeskal, M. Bazzi, G. Beer, L. Bombelli, A.M. Bragadireanu, P. Bühler, M. Cargnelli, C. Fiorini, C. Guaraldo, R. Hayano, M. Iliescu, T. Ishiwatari, M. Iwasaki, P. Kienle, A. Longoni, V. Lucherini, J. Márton, K. Nikolics, S. Okada, D. Pietreanu, T. Ponta, A. Romero Vidal, P. Levi Sandri, A. Scordo, D. Sirghi, F. Sirghi, K. Suzuki, H. Tatsuno, O. Vázquez Doce, E. Widmann

Bibliographic record

VenueInternational Journal of Modern Physics A · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversity of Victoria
FundersUniversität Wien
KeywordsPhysicsExotic atomNuclear physicsColliderStrangenessHadronElectronHadron spectroscopyParticle physicsAtom (system on chip)Hydrogen atomHydrogenAtomic physicsQuantum mechanicsMuonGroup (periodic table)

Abstract

fetched live from OpenAlex

With precision X-ray spectroscopy of kaonic hydrogen at the DAΦNE electron-positron collider at Laboratori Nazionali di Frascati the chiral symmetry breaking scenario in the strangeness sector will be investigated by studying the K-p s-wave interaction at threshold. This is possible by observing the strong interaction induced shift and width of the 1s state in kaonic hydrogen atoms. The results of the first measurement at LNF with DEAR (DAΦNE Exotic Atom Research) will be given and the new SIDDHARTA (Silicon Drift Detector for Hadronic Atom Research with Timing Application) project will be described, which is aiming at a substantial improvement of the preceding DEAR result.

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)0.001
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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.293
Teacher spread0.278 · 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

Citations5
Published2009
Admission routes1
Has abstractyes

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