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Current Status of inclusive hadronic tau determinations of |V_us|

2019· article· en· W2917460080 on OpenAlexafffund
Kim Maltman, P. A. Boyle, Renwick J. Hudspith, Taku Izubuchi, Andreas Jüttner, Christoph Lehner, Randy Lewis, Antonin Portelli, Matthew Spraggs, J. M. Zanotti

Bibliographic record

VenueSciPost Physics Proceedings · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsYork University
FundersBrookhaven National LaboratoryAustralian Research CouncilRIKENScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaU.S. Department of EnergySeventh Framework ProgrammeJapan Society for the Promotion of ScienceOffice of ScienceSteno Diabetes Center Copenhagen
KeywordsAlgorithmPhysicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

We review the status of the determination of \vert V_{us}\vert <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo stretchy="false" form="postfix">|</mml:mo> <mml:msub> <mml:mi>V</mml:mi> <mml:mrow> <mml:mi>u</mml:mi> <mml:mi>s</mml:mi> </mml:mrow> </mml:msub> <mml:mo stretchy="false" form="postfix">|</mml:mo> </mml:mrow> </mml:math> from both flavor-breaking finite-energy sum rules based on inclusive non-strange and strange hadronic \tau <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>τ</mml:mi> </mml:math> decay data and the recent lattice-based analysis of inclusive strange hadronic \tau <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>τ</mml:mi> </mml:math> decay data. In particular, we update the results from these analysis frameworks taking into account recent improvements to a number of strange branching fractions reported by HFLAV at CKM2018 and this meeting. We find that inclusive \tau <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>τ</mml:mi> </mml:math> decay data yields results for \vert V_{us}\vert <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo stretchy="false" form="postfix">|</mml:mo> <mml:msub> <mml:mi>V</mml:mi> <mml:mrow> <mml:mi>u</mml:mi> <mml:mi>s</mml:mi> </mml:mrow> </mml:msub> <mml:mo stretchy="false" form="postfix">|</mml:mo> </mml:mrow> </mml:math> compatible within errors with the expectations of three-family unitarity.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.577

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 head0.009
GPT teacher head0.287
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations9
Published2019
Admission routes2
Has abstractyes

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