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Record W4379882375 · doi:10.22323/1.417.0010

Highlights from VERITAS

2023· article· en· W4379882375 on OpenAlexfundno aff
J. Quinn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Energy Research Scientific Computing CenterU.S. Department of EnergyOffice of ScienceSmithsonian InstitutionNational Science Foundation
KeywordsPhysicsAstronomyAstroparticle physicsCherenkov radiationPulsarAstrophysicsCherenkov Telescope ArrayGamma-ray astronomyGalaxyGalactic astronomyBlazarRadio astronomyActive galactic nucleusSupernovaExtragalactic astronomyLIGOHigh-energy astronomyGamma rayCosmic rayMilky WayDetectorGravitational waveOptics

Abstract

fetched live from OpenAlex

VERITAS is one of the world’s most sensitive detectors of astrophysical VHE (E > 100 GeV) gamma rays. This array of four 12-m imaging atmospheric Cherenkov telescopes, located in southern Arizona, USA, has operated for ~15 years. VERITAS science spans Galactic topics, including pulsar wind nebulae, binary systems, and supernova remnants; extra-galactic topics, including studies of blazars and radio galaxies, searches for gamma-ray bursts and fast radio bursts; multi-messenger science; and astroparticle physics topics including searches for dark matter. VERITAS has also pioneered the use of IACTs for optical astronomy, particularly via intensity interferometry. Recent highlights from the VERITAS observing program and scientific results are presented.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0020.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0580.024

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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