MétaCan
Menu
Back to cohort
Record W7052668861

Search for scalar bottom quarks from gluino decays in (p)over-barp collisions at root s=1.96 TeV

2006· article· en· W7052668861 on OpenAlexfundno aff

Bibliographic record

VenuePurdue e-Pubs (Purdue University System) · 2006
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaIstituto Nazionale di Fisica NucleareNational Science CouncilAlfred P. Sloan FoundationFermilabU.S. Department of EnergySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungRussian Foundation for Basic ResearchMinistry of Education, Culture, Sports, Science and TechnologyNational Science Foundation
KeywordsGluinoCollider Detector at FermilabHadronizationTop quarkQuarkBottom quarkScalar (mathematics)Standard Model (mathematical formulation)
DOInot available

Abstract

fetched live from OpenAlex

We searched for scalar bottom quarks in 156 pb(-1) of (P) over barp collisions at root s =1.96 TeV recorded by the Collider Detector at Fermilab II experiment at the Tevatron. Scalar bottom quarks can be produced from gluino decays in R-parity conserving models of supersymmetry when the mass of the gluino exceeds that of the scalar bottom quark. Then, a scalar bottom quark can decay into a bottom quark and a neutralino. To search for this scenario, we investigated events with large missing transverse energy and at least three jets, two or more of which were identified as containing a secondary vertex from the hadronization of b quarks. We found four candidate events, where 2.6 +/- 0.7 are expected from standard model processes, and placed 95% confidence level lower limits on gluino and scalar bottom quark masses of up to 280 and 240 GeV/c(2), respectively.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.187
Teacher spread0.180 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venuePurdue e-Pubs (Purdue University System)Same topicPlasma Diagnostics and ApplicationsFrench-language works237,207