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Record W2949426245 · doi:10.1134/s1063779611040125

Dark matter search experiments

2011· article· en· W2949426245 on OpenAlexaff
Wolfgang Rau

Bibliographic record

VenuePhysics of Particles and Nuclei · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsQueen's University
Fundersnot available
KeywordsPhysicsDark matterWeakly interacting massive particlesAnnihilationScalar field dark matterMixed dark matterUniverseAstrophysicsLight dark matterGravitationCosmologyParticle physicsTheoretical physicsAstronomyDark energy

Abstract

fetched live from OpenAlex

Astronomical and cosmological observations of the past 80 years build solid evidence that atomic matter makes up only a small fraction of the matter in the universe. The dominant fraction does not interact with electromagnetic radiation, does not absorb or emit light and hence is called Dark Matter. So far dark matter has revealed its existence only through gravitational effects. The strongest experimental effort to find other evidence and learn more about the nature of the dark matter particles concentrates around Weakly Interacting Massive Particles which are among the best motivated dark matter candidates. The two main groups of experiments in this field aim for indirect detection through annihilation products and direct detection via interactions with atomic matter respectively. The experimental sensitivity is starting to reach the parameter range which is preferred by theoretical considerations and we can expect to confirm or dismiss some of the most interesting theoretical models in the next few years.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0250.006

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 head0.035
GPT teacher head0.260
Teacher spread0.225 · 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 designObservational
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

Citations13
Published2011
Admission routes1
Has abstractyes

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