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Record W6983371160

Measurement of the inclusive jet cross section at the Fermilab Tevatron p(p)over-bar collider using a cone-based jet algorithm

2008· article· en· W6983371160 on OpenAlexfundno aff

Bibliographic record

VenuePurdue e-Pubs (Purdue University System) · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsnot available
FundersFermilabScience and Technology Facilities CouncilAlfred P. Sloan FoundationNational Science CouncilNatural Sciences and Engineering Research Council of CanadaIstituto Nazionale di Fisica NucleareCentre National de la Recherche ScientifiqueU.S. Department of EnergySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungRussian Foundation for Basic ResearchMinistry of Education, Culture, Sports, Science and TechnologyNational Science Foundation
KeywordsTevatronJet (fluid)RapidityPartonCross section (physics)Quantum chromodynamicsFermilabColliderCollider Detector at Fermilab
DOInot available

Abstract

fetched live from OpenAlex

We present a measurement of the inclusive jet cross section in p (p) over bar collisions at root s = 1.96 TeV based on data collected by the CDF II detector with an integrated luminosity of 1.13 fb(-1). The measurement was made using the cone-based midpoint jet clustering algorithm in the rapidity region of vertical bar y vertical bar < 2.1. The results are consistent with next-to-leading-order perturbative QCD predictions based on recent parton distribution functions (PDFs), and are expected to provide increased precision in PDFs at high parton momentum fraction x. The results are also compared to the recent inclusive jet cross section measurement using the k(T) jet clustering algorithm, and we find that the ratio of the cross sections measured with the two algorithms is in agreement with theoretical expectations over a large range of jet transverse momentum and rapidity.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score1.000

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.233
Teacher spread0.216 · 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.

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

Citations0
Published2008
Admission routes1
Has abstractyes

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