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Tuning Herwig 7 with Lund String Model

2024· article· en· W4392666041 on OpenAlexaff
Prantik Sarmah, Andrzej Siódmok, Michaela Divisova, M. Myška

Bibliographic record

VenueActa Physica Polonica B Proceedings Supplement · 2024
Typearticle
Languageen
FieldMathematics
TopicMathematics and Applications
Canadian institutionsUniversity of Alberta
FundersAcademic Computer Centre Cyfronet, AGH University of Science and TechnologyInfrastruktura PL-Grid
KeywordsString (physics)PhysicsComputer scienceTheoretical physics

Abstract

fetched live from OpenAlex

We present selected results of a systematic study of non-perturbative effects of the Lund string hadronization model from Pythia 8 on top of the angular ordered parton shower in the Herwig 7 Monte Carlo Event Generator. We adopt the Professor approach to tune a set of model parameters to lepton- and hadron-collision data and compare obtained results to the default Herwig 7 tune, the Autotunes tune as well as the Pythia 8 tune.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.900

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 studies0.0000.000
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 head0.046
GPT teacher head0.323
Teacher spread0.277 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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