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Record W2214368200 · doi:10.22323/1.236.0854

Raster Scanning the Crab Nebula to Produce an Extended VHE Calibration Source

2016· preprint· en· W2214368200 on OpenAlexfundno aff
R. Bird

Bibliographic record

VenueProceedings of The 34th International Cosmic Ray Conference — PoS(ICRC2015) · 2016
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsnot available
FundersEuropean Regional Development FundNatural Sciences and Engineering Research Council of CanadaU.S. Department of EnergyOffice of ScienceSmithsonian InstitutionNational Science Foundation
KeywordsCrab NebulaCalibrationRaster graphicsPoint sourceRaster scanNebulaPhysicsAstrophysicsComputer scienceOpticsGamma rayComputer graphics (images)

Abstract

fetched live from OpenAlex

The Crab Nebula has long been the standard reference point source for very-high-energy (VHE, E $>$100 GeV) gamma-ray observatories such as VERITAS. It has enabled testing and improvement of analysis methods, validation of techniques, and has served as a calibration source. No comparable extended source is known with a high, constant flux and well understood morphology. In order to artificially generate such a source, VERITAS has performed raster scans across the Crab Nebula. By displacing the source within the field-of-view in a known pattern, it is possible to generate an extended calibration source for verification of extended source analysis techniques. The method as well as early results of this novel technique 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.258
Teacher spread0.238 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations1
Published2016
Admission routes1
Has abstractyes

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