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Record W2980537172 · doi:10.1051/epjconf/201921802001

CMD-3 Overview

2019· article· en· W2980537172 on OpenAlexaff
Ivan Logashenko, F.V. Ignatov, R.R. Akhmetshin, Artem Amirkhanov, A. V. Anisenkov, V.M. 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, V. L. Ivanov, S.V. Karpov, V. F. Kazanin, A. N. Kirpotin, A. Korobov, I. A. Koop, A. Kozyrev, E. A. Kozyrev, P. Krokovny, A.E. Kuzmenko, A. Kuzmin, P.A. Lukin, K. Mikhailov, V.S. Okhapkin, A.V. Otboev, Yu.N. Pestov, A.S. Popov, G.P. Razuvaev, A.A. Ruban, N.M. Ryskulov, A.E. Ryzhenenkov, A. I. Senchenko, V. Shebalin, D.N. Shemyakin, B. Shwartz, D. B. Shwartz, A.L. Sibidanov, P. Yu. Shatunov, Yu. M. Shatunov, E. P. Solodov, A. A. Talyshev, A.I. Vorobiov, Yu. V. Yudin, I. M. Zemlyansky

Bibliographic record

VenueEPJ Web of Conferences · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversity of Victoria
FundersRussian Science FoundationRussian Foundation for Basic Research
KeywordsUpgradePhysicsNuclear physicsMuonCalorimeter (particle physics)DetectorColliderHadronTracking (education)Particle physicsRange (aeronautics)Energy (signal processing)Center of mass (relativistic)Aerospace engineeringComputer scienceOpticsEngineering

Abstract

fetched live from OpenAlex

The CMD-3 detector is installed at the VEPP-2000 e+e− collider at BINP (Novosibirsk, Russia). It is a general-purpose detector, equipped with a tracking system, two crystal (CSI and BGO) calorimeters, liquid Xe calorimeter, TOF and muon systems. The main goal of experiments at CMD-3 is a study of exclusive modes of e+e−→ hadrons at energies $ \sqrt s \le $ GeV. In particular, these results provide an important input for calculation of the hadronic contribution to the muon anomalous magnetic moment. The first round of data taking was performed in 2011–2013, when about 60 1/pb were taken in the center-of-mass (c.m.) energy range from 0.32 to 2.0 GeV. Here we present a survey of results of data analysis. Between 2013 and 2016 the collider and the detector were upgraded. The data taking resumed by the end of 2016. In the first run after the upgrade about 50 1/pb were collected at the energy range between 1.28 and 2.007 GeV. We discuss the upgrade and the first preliminary results from the new data.

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)0.005
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0060.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0640.050

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 head0.023
GPT teacher head0.282
Teacher spread0.260 · 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
GenreOther

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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