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Measurement of the centrality dependence of charged particle pseudorapidity distribution in proton–lead collisions at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"><mml:msqrt><mml:msub><mml:mrow><mml:mi>s</mml:mi></mml:mrow><mml:mrow><mml:mtext>NN</mml:mtext></mml:mrow></mml:msub></mml:msqrt><mml:mo>=</mml:mo><mml:mn>5.02</mml:mn><mml:mspace width="0.25em"/><mml:mtext>TeV</mml:mtext></mml:math> with the ATLAS detector

2014· article· lv· W1999914258 on OpenAlexfundno aff
R. R. Debbe

Bibliographic record

VenueNuclear Physics A · 2014
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsInstitut National de Physique Nucléaire et de Physique des ParticulesMax-Planck-GesellschaftCentre National de la Recherche ScientifiqueBritish Columbia Knowledge Development FundFundação para a Ciência e a TecnologiaAgencia Nacional de Promoción Científica y TecnológicaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungScience and Technology Facilities CouncilBundesministerium für Bildung und ForschungMinistry of Education, Culture, Sports, Science and TechnologyNatural Sciences and Engineering Research Council of CanadaDepartment of Science and Technology, Ministry of Science and Technology, IndiaH. Lundbeck A/SFondation Partager le SavoirEuropean Social FundCentre National pour la Recherche Scientifique et TechniqueGeorgian National Science FoundationJapan Society for the Promotion of ScienceNational Research Center "Kurchatov Institute"Israel Science FoundationU.S. Department of EnergyIsraeli Centers for Research ExcellenceComisión Nacional de Investigación Científica y TecnológicaTürkiye Atom Enerjisi KurumuJoint Institute for Nuclear ResearchMinisterstwo Edukacji i NaukiConselho Nacional de Desenvolvimento Científico e TecnológicoBundesministerium für Wissenschaft, Forschung und WirtschaftFonds Québécois de la Recherche sur la Nature et les TechnologiesAustrian Science FundOntario Innovation TrustNational Natural Science Foundation of ChinaLeverhulme TrustEuropean CommissionFundação de Amparo à Pesquisa do Estado de São PauloJavna Agencija za Raziskovalno Dejavnost RSDeutsche ForschungsgemeinschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekAgence Nationale de la RechercheServices Fédéraux des Affaires Scientifiques, Techniques et CulturellesGeneral Secretariat for Research and TechnologyDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)CERNDanmarks GrundforskningsfondAlexander von Humboldt-StiftungNational Science FoundationLundbeckfondenCompute CanadaCanarie
KeywordsPseudorapidityMultiplicity (mathematics)Charged particlePhysicsGlauberLarge Hadron ColliderNuclear physicsMonte Carlo methodCentralityRapidityParticle physicsCollisionStatistical physicsCombinatoricsMathematicsComputer scienceGeometryStatisticsOpticsIon

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.021
GPT teacher head0.243
Teacher spread0.222 · 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 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

Citations5
Published2014
Admission routes1
Has abstractno

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