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Dark matter searches with the PICASSO experiment at SNOLAB

2008· article· en· W2069643158 on OpenAlexaffabout
Berta Beltrán

Bibliographic record

VenueJournal of Physics Conference Series · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPICASSODark matterAstrophysicsPhysicsArtVisual arts

Abstract

fetched live from OpenAlex

Recent cosmological observations support the existence of dark matter as a significant constituent of the universe. The PICASSO experiment (Project in CAnada to Search for Supersymmetric Objects) uses super-heated C4F10 droplets suspended in a gel as a target sensitive to WIMP-proton spin-dependent elastic scattering. A 19F recoiling nucleus produces a heat spike in the droplet which triggers its full explosive evaporation. The phase transition is accompanied by a shock wave which is recorded by as set of piezoelectric transducers attached to the detector. A first phase of the experiment in SNOLAB used 19.3 g of active mass and was operated for half a year in 2004 (Phys. Lett. B 2005). The phase II setup has been improved substantially in sensitivity by using an array of 32 detectors with an active mass of 80g each and largely reduced background. A more precise control of the temperature and pressure of the detectors allows for reduced systematic errors in the final result. This poster will show the quality of the data taken during one year by the first set of phase II detectors installed underground, together with their expected sensitivity in the spin dependent sector.

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)0.002
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: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.256
Teacher spread0.231 · 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

Citations2
Published2008
Admission routes2
Has abstractyes

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