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Record W248270836 · doi:10.2172/1128082

Search for Standard Model Higgs Boson Produced in Association with a Top-Antitop Quark Pair in 1.96 TeV Proton-Antiproton Collisions

2007· report· en· W248270836 on OpenAlexaff
Stanley Lai

Bibliographic record

Venuenot available
Typereport
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsParticle physicsPhysicsHiggs bosonTop quarkStandard Model (mathematical formulation)Collider Detector at FermilabLuminosityAntiprotonNuclear physicsFermilabProduction (economics)Pair productionColliderBottom quarkQuarkLarge Hadron ColliderProtonTevatronAstrophysics

Abstract

fetched live from OpenAlex

This thesis describes the first search for Standard Model Higgs boson production in association with a top-antitop quark pair in proton-antiproton collisions at a centre of mass energy of 1.96 TeV. The integrated luminosity for othis search corresponds to 319 pb-1 of data recorded by the Collider Detector at Fermilab. We outline the even selection criteria, evaluate the even acceptance and estimate backgrounds from Standard Model sources. These events are observed that satisfy our event selection, while 2.16 ± 0.66 events are expected from background processes. no significant excess of events above background is thus observed, and we set 95% confidence level upper limits on the production cross section for this process as a function of the Higgs mass. For a Higgs boson mass of 115 GeV/c2 we find that σ$t\bar{t}H$ x BR (H → bb) < 690 fb at 95% C.L. These are the first limits set for $t\bar{t}H$ production. This search also allows us to anticipate the challenges and necessary strategies needed for future searches of $t\bar{t}H$ production.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models splitAgreement compares identical category sets and study designs across arms.

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: 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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.347
Teacher spread0.312 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designBench or experimental · Observational
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
Published2007
Admission routes1
Has abstractyes

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