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Light mixed sneutrinos as thermal dark matter

High Energy Physics - Phenomenology · Submitted 3 Aug 2010

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim In supersymmetric models with Dirac neutrino masses, a left-right mixed sneutrino can be a viable dark matter candidate.

how it is stated · hedged possibility 0.59 read the record →

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arXiv ID1008.0580 (version 2)
Pith IDG6NCTLUN, Pith's permanent record of this paper and its review
CitationA. Pukhov, E. K. Park, G. Belanger, M. Kakizaki, S. Kraml. "Light mixed sneutrinos as thermal dark matter." arXiv:1008.0580 (2010). https://pith.science/paper/G6NCTLUN
Claim paper

The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 2,931 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.38 · human participants 0.01 · controlled comparison 0.02 · randomized assignment 0.01 · states quantitative result 0.59 · compares with prior results 0.07 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

In supersymmetric models with Dirac neutrino masses, a left-right mixed sneutrino can be a viable dark matter candidate. We examine the MSSM+$\tilde\nu_R$ parameter space where this is the case with particular emphasis on light sneutrinos with masses below 10 GeV. We discuss implications for direct and indirect dark matter searches, including the relevant uncertainties, as well as consequences for collider phenomenology.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 In supersymmetric models with Dirac neutrino masses, a left-right mixed sneutrino can be a viable dark matter candidate. background 1.00 0.08 0.46 hedged possibility 0.59
s1 We examine the MSSM+$\tilde\nu_R$ parameter space where this is the case with particular emphasis on light sneutrinos with masses below 10 GeV. contribution 0.97 0.88 0.09 asserted 0.77
s2 We discuss implications for direct and indirect dark matter searches, including the relevant uncertainties, as well as consequences for collider phenomenology. contribution 0.78 0.70 0.08 asserted 0.65

What kind of paper the classifier reports this is: theoretical result 0.94 · evidence from argument 0.50.

What was examined, and what was not

sources read
  • arXiv listing abstract v2
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

In supersymmetric models with Dirac neutrino masses, a left-right mixed sneutrino can be a viable dark matter candidate. We examine the MSSM+$\tilde\nu_R$ parameter space where this is the case with particular emphasis on light sneutrinos with masses below 10 GeV. We discuss implications for direct and indirect dark matter searches, including the relevant uncertainties, as well as consequences for collider phenomenology.

Human review
References
How the literature uses it

31 arXiv papers cite this in 66 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it · 43 sentences without a confident label

Contests it 1 paper
Uses its method or tool 6 papers
Uses its data or values 1 paper
Compares with it 1 paper
Cites it as support 1 paper
Cites it as background 11 papers

What it cites · 71 sentences without a confident label

Contests 2 papers
Uses the method or tool of 7 papers
Uses data or values from 11 papers
Compares with 4 papers
Cites as background 3 papers

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