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Record W4391819804 · doi:10.1007/jhep02(2024)081

Dynamical inflation stimulated cogenesis

2024· article· en· W4391819804 on OpenAlexafffund
Debasish Borah, Arnab Dasgupta, Daniel Stolarski

Bibliographic record

VenueJournal of High Energy Physics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsCarleton University
FundersScience and Engineering Research BoardNatural Sciences and Engineering Research Council of CanadaUniversity of California, San Diego
KeywordsPhysicsInflation (cosmology)Theoretical physicsMathematical physicsParticle physicsQuantum electrodynamics

Abstract

fetched live from OpenAlex

A bstract We propose a minimal setup that realises dynamical inflection point inflation, and, using the same field content, generates neutrino masses, a baryon asymmetry of the universe, and dark matter. A dark SU(2) D gauge sector with a dark scalar doublet playing the role of inflaton is considered along with several doublet and singlet fermions sufficient to realise multiple inflection points in the inflaton potential. The singlet fermions couple to SM leptons and generate neutrino masses via the inverse seesaw mechanism. Those fermions also decay asymmetrically and out of equilibrium, generating a baryon asymmetry via leptogenesis. Some of the fermion doublets are dark matter, and they are produced via inflaton decay and freeze-in annihilation of the same fermions that generate the lepton asymmetry. Reheating, leptogenesis, and dark matter are all at the TeV scale.

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.006
GPT teacher head0.242
Teacher spread0.236 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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