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Record W4404403263 · doi:10.1139/cjp-2024-0131

Direct detection searches for dark matter particles using superheated bubble chambers and cryogenic liquid argon detectors

2024· article· en· W4404403263 on OpenAlexafffundvenueabout
C. B. Krauss, S. Viel

Bibliographic record

VenueCanadian Journal of Physics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsCarleton UniversityUniversity of Alberta
FundersAlliance de recherche numérique du CanadaOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaQueen's UniversityLeibniz-GemeinschaftMinistry of Advanced Education, Government of AlbertaCanada First Research Excellence FundUniversity of AlbertaWestern Canada Research Grid
KeywordsPhysicsDark matterDetectorBubbleBubble chamberSuperheatingNuclear physicsCryogenicsArgonAstrophysicsParticle physicsOpticsAtomic physicsMechanicsCondensed matter physicsThermodynamics

Abstract

fetched live from OpenAlex

This review spotlights Canadian participation to experiments aimed at the direct detection of dark matter particles, with sensitivity over a mass range from the GeV scale to the Planck scale. Two technologies are discussed: superheated bubble chambers (PICASSO, COUPP, PICO, scintillating bubble chamber) and cryogenic liquid argon detectors (DEAP, DarkSide, ARGO). We present the recent history, current status, and future plans of these research endeavours.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.236
Teacher spread0.216 · 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 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

Citations0
Published2024
Admission routes4
Has abstractyes

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