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Study of the process e+e−→π+π−π0η in the c.m. energy range 1394–2005 MeV with the CMD-3 detector

2017· article· en· W3196504846 on OpenAlexaff
R.R. Akhmetshin, Artem Amirkhanov, A. V. Anisenkov, V. Aulchenko, V.Sh. Banzarov, N.S. Bashtovoy, D. E. Berkaev, A. Bondar, A.V. Bragin, S.I. Eidelman, D. Epifanov, L.B. Epshteyn, A.L. Erofeev, G.V. Fedotovich, S.E. Gayazov, A.A. Grebenuk, S.S. Gribanov, D.N. Grigoriev, F.V. Ignatov, V. L. Ivanov, S.V. Karpov, V. F. Kazanin, I. A. Koop, A. N. Kirpotin, A. Korobov, A.N. Kozyrev, E. A. Kozyrev, P. Krokovny, A.E. Kuzmenko, Alexander Kuzmin, I.B. Logashenko, P.A. Lukin, K. Mikhailov, V.S. Okhapkin, A.V. Otboev, Yu.N. Pestov, A.S. Popov, G.P. Razuvaev, Yu. A. Rogovsky, A.A. Ruban, N.M. Ryskulov, A.E. Ryzhenenkov, A. I. Senchenko, Yu. M. Shatunov, P. Yu. Shatunov, V. Shebalin, D.N. Shemyakin, B.A. Shwartz, D. B. Shwartz, A.L. Sibidanov, E. P. Solodov, В.М. Титов, Alexei Talyshev, A.I. Vorobiov, I. M. Zemlyansky, Yu. V. Yudin

Bibliographic record

VenuePhysics Letters B · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Chromodynamics and Particle Interactions
Canadian institutionsUniversity of Victoria
FundersRussian Science FoundationRussian Foundation for Basic Research
KeywordsOmegaPhysicsColliderRange (aeronautics)DetectorPiEnergy (signal processing)Atomic physicsElectron–positron annihilationNuclear physicsIntermediate stateAnalytical Chemistry (journal)ChemistryOpticsMaterials scienceHadronQuantum mechanics

Abstract

fetched live from OpenAlex

The cross section of the process e + e − → π + π − π 0 η has been measured using a data sample of 21.8 pb − 1 collected with the CMD-3 detector at the VEPP-2000 e + e − collider. 2769 ± 95 signal events have been selected in the center-of-mass energy range 1394–2005 MeV. The production dynamics is dominated by the ω ( 782 ) η and ϕ ( 1020 ) η intermediate states in the lower energy range, and by the a 0 ( 980 ) ρ ( 770 ) intermediate state at higher energies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.390

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.265
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 designObservational
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

Citations40
Published2017
Admission routes1
Has abstractyes

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