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Record W2918646092 · doi:10.1088/1674-1137/43/5/054104

Hadronization from color interactions *

2019· article· en· W2918646092 on OpenAlexaff

Bibliographic record

VenueChinese Physics C · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsHadronizationPseudorapidityHadronQuarkMultiplicity (mathematics)Coalescence (physics)Monte Carlo methodEvent generator

Abstract

fetched live from OpenAlex

Abstract A quark coalescence model, based on semi-relativistic molecular dynamics with color interactions among quarks, is presented and applied to pp collisions. A phenomenological potential with two tunable parameters is introduced to describe the color interactions between quarks and antiquarks. The interactions drive the process of hadronization that finally results in different color neutral clusters, which can be identified as hadrons based on some criteria. A Monte Carlo generator PYTHIA is used to generate quarks in the initial state of hadronization, and different values of tunable parameters are used to study the final state distributions and correlations. Baryon-to-meson ratio, transverse momentum spectra, pseudorapidity distributions and forward-backward multiplicity correlations of hadrons produced in the hadronization process, obtained from this model with different parameters, are compared with those from PYTHIA.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.288
Teacher spread0.279 · 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 designTheoretical or conceptual
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
Published2019
Admission routes1
Has abstractyes

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