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Record W1540557790 · doi:10.1051/epjconf/20159504020

PICASSO, COUPP and PICO - search for dark matter with bubble chambers

2015· article· en· W1540557790 on OpenAlexafffundabout
C. Amole, M. Ardid, D. M. Asner, D. Baxter, E. Behnke, Pijushpani Bhattacharjee, H. Borsodi, M. Bou-Cabo, S. J. Brice, D. Broemmelsiek, K. Clark, J. I. Collar, P. S. Cooper, M. B. Crisler, C. E. Dahl, Mala Das, F. Debris, N. Dhungana, J. Farine, I. Felis, R. Filgas, Mirjam Fines-Neuschild, F. Girard, G. Giroux, M. Hai, J. Hall, O. Harris, C. M. Jackson, Miaochen Jin, C. B. Krauss, M. Lafrenière, M. Laurin, I. Lawson, I. Levine, W. H. Lippincott, E. Mann, J.P. Martin, Deepam Maurya, P. Mitra, R. Neilson, A. J. Noble, A. Plante, R.B. Podviyanuk, Shashank Priya, Alan Robinson, M. Ruschman, O. Scallon, S. Seth, A. Sonnenschein, N. Starinski, I. Štekl, E. Vázquez-Jáuregui, Joshua Wells, U. Wichoski, V. Zacek, J. Zhang

Bibliographic record

VenueEPJ Web of Conferences · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsUniversity of AlbertaUniversité de MontréalLaurentian UniversityUniversity of TorontoSnolabQueen's University
FundersPacific Northwest National LaboratoryNatural Sciences and Engineering Research Council of CanadaOffice of ScienceNational Science FoundationMinisterio de Economía y CompetitividadBattelleFermilabHigh Energy PhysicsU.S. Department of EnergyUniversity of Chicago
KeywordsPhysicsDark matterWeakly interacting massive particlesNuclear physicsDetectorParticle physicsSuperheatingBubble chamberCold dark matterAstrophysicsOpticsCosmologyDark energyScalar field dark matter

Abstract

fetched live from OpenAlex

The PICASSO and COUPP collaborations use superheated liquid detectors to search for cold dark matter through the direct detection of weakly interacting massive particles (WIMPs). These experiments, located in the underground laboratory of SNOLAB, Canada, detect phase transitions triggered by nuclear recoils in the keV range induced by interactions with WIMPs. We present details of the construction and operation of these detectors as well as the results, obtained by several years of observations. We also introduce PICO, a joint effort of the two collaborations to build a second generation ton-scale bubble chamber with 250 liters of active liquid.

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)0.002
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.025
GPT teacher head0.257
Teacher spread0.232 · 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

Citations11
Published2015
Admission routes3
Has abstractyes

Explore more

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