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A connection between the high energy-scale evolution of the P- and T-odd π<i>NN</i>coupling constant and the strong π<i>NN</i>interaction

2008· article· en· W2083673808 on OpenAlexafffund
P. G. Blunden, S. Kondratyuk

Bibliographic record

VenueJournal of Physics G Nuclear and Particle Physics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Chromodynamics and Particle Interactions
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPseudoscalarPhysicsCoupling constantVertex (graph theory)PseudovectorPionAsymptotic freedomRenormalizationConstant (computer programming)Particle physicsHadronConnection (principal bundle)Renormalization groupNucleonMathematical physicsScale (ratio)Coupling (piping)Quantum chromodynamicsQuantum mechanicsQuarkCombinatoricsMathematicsGeometryMesonGraph

Abstract

fetched live from OpenAlex

The large energy-scale behaviour of the parity and time-reversal violating (PTV) pion-nucleon coupling constant is analyzed in a model combining renormalization-group techniques and the dressing of the PTV vertex with a pion loop. With the strong $\pi N N$ vertex as a mixture of the pseudovector and pseudoscalar couplings, we show that depending on the admixture parameter, two qualitatively distinct types of behaviour are obtained for the PTV coupling constant at high energy scales: an asymptotic freedom or a fixed-point. We find a critical value of the admixture parameter which delineates these two scenarios. Several examples of the high-energy scale behaviour of the PTV $\pi N N$ constant are considered, corresponding to realistic hadronic models of the strong pion-nucleon interaction.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score0.428

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 studies0.0010.000
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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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 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
Published2008
Admission routes2
Has abstractyes

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