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Record W6976524384 · doi:10.60692/9eg97-r3y02

Search for an additional, heavy Higgs boson in the $$H\rightarrow ZZ$$ H → Z Z decay channel at $$\sqrt{s} = 8\;\text{ TeV }$$ s = 8 TeV in $$pp$$ p p collision data with the ATLAS detector

2016· article· en· W6976524384 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicArt, Technology, and Culture
Canadian institutionsMcGill University
Fundersnot available
KeywordsHiggs bosonLarge Hadron ColliderBranching fractionStandard Model (mathematical formulation)BosonLuminosityHadronATLAS experiment

Abstract

fetched live from OpenAlex

A search is presented for a high-mass Higgs boson in the [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] decay modes using the ATLAS detector at the CERN Large Hadron Collider. The search uses proton-proton collision data at a centre-of-mass energy of 8 TeV corresponding to an integrated luminosity of 20.3 fb[Formula: see text]. The results of the search are interpreted in the scenario of a heavy Higgs boson with a width that is small compared with the experimental mass resolution. The Higgs boson mass range considered extends up to [Formula: see text] for all four decay modes and down to as low as 140 [Formula: see text], depending on the decay mode. No significant excess of events over the Standard Model prediction is found. A simultaneous fit to the four decay modes yields upper limits on the production cross-section of a heavy Higgs boson times the branching ratio to [Formula: see text] boson pairs. 95 % confidence level upper limits range from 0.53 pb at [Formula: see text] GeV to 0.008 pb at [Formula: see text] GeV for the gluon-fusion production mode and from 0.31 pb at [Formula: see text] GeV to 0.009 pb at [Formula: see text] GeV for the vector-boson-fusion production mode. The results are also interpreted in the context of Type-I and Type-II two-Higgs-doublet models.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.064
GPT teacher head0.236
Teacher spread0.173 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2016
Admission routes1
Has abstractyes

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