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Multiplicity dependence of ϒ production at forward rapidity in pp collisions at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:msqrt><mml:mrow><mml:mi>s</mml:mi></mml:mrow></mml:msqrt><mml:mo linebreak="goodbreak" linebreakstyle="after">=</mml:mo><mml:mn>13</mml:mn></mml:math> TeV

2024· article· lv· W4405634995 on OpenAlexaff
S. Acharya, D. Adamová, A. Adler, G. Aglieri Rinella, M. Agnello, N. Agrawal, Z. Ahammed, S. Ahmad, S. U. Ahn, I. Ahuja, A. Akindinov, M. Al-Turany, H. M. Alfanda

Bibliographic record

VenueNuclear Physics B · 2024
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsInstitute of Particle Physics
FundersNuclear PhysicsNational Research, Development and Innovation OfficeInstitut National de Physique Nucléaire et de Physique des ParticulesConsejo Nacional de Ciencia y TecnologíaDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoTürkiye Enerji, Nükleer ve Maden Araştırma KurumuFondo de Cooperación Internacional en Ciencia y TecnologíaState Committee of ScienceNorges ForskningsrådVetenskapsrådetFinanciadora de Estudos e ProjetosSuranaree University of TechnologyVillum FondenJapan Society for the Promotion of ScienceConselho Nacional de Desenvolvimento Científico e TecnológicoGeneral Secretariat for Research and TechnologyDanmarks GrundforskningsfondMinisterstvo školstva, vedy, výskumu a športu Slovenskej republikyPontificia Universidad Católica del PerúNational Research FoundationAustrian Science FundKorea Institute of Science and TechnologyFP7 International CooperationMinistry of Education, Culture, Sports, Science and TechnologyBundesministerium für Bildung und ForschungU.S. Department of EnergyNational Research Foundation of KoreaNational Science and Technology Development AgencyNational Natural Science Foundation of ChinaGSI Helmholtzzentrum für SchwerionenforschungDanmarks Frie ForskningsfondÖsterreichischen Akademie der WissenschaftenEuropean CommissionFundação de Amparo à Pesquisa do Estado de São PauloKorea Institute of Science and Technology InformationNederlandse Organisatie voor Wetenschappelijk OnderzoekDepartment of Atomic Energy, Government of IndiaMinistry of Education of the People's Republic of ChinaScience and Technology Facilities CouncilHrvatska Zaklada za ZnanostBadan Riset dan Inovasi NasionalUniversity Grants CommissionIstituto Nazionale di Fisica NucleareDepartment of Science and Technology, Ministry of Science and Technology, IndiaCentre National de la Recherche ScientifiqueCouncil of Scientific and Industrial Research, IndiaStrongUniversidade Federal do Rio Grande do SulCERNCentro de Aplicaciones Tecnológicas y Desarrollo NuclearNational Science Foundation
KeywordsMultiplicity (mathematics)RapidityComputer scienceMathematicsPhysicsNuclear physicsMathematical analysis

Abstract

fetched live from OpenAlex

International audience

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.005

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 head0.019
GPT teacher head0.255
Teacher spread0.236 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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