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Record W4380677515 · doi:10.1103/physrevd.107.103056

Greisen function and its ability to describe air-shower profiles

2023· article· en· W4380677515 on OpenAlexaff
Maximilian Stadelmaier, J. Vícha, Vladimír Novotný

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsInstitute of Particle Physics
FundersGrantová Agentura České RepublikyMinisterstvo Školství, Mládeže a TělovýchovyEuropean Commission
KeywordsCosmic rayPhysicsAir showerShowerPierre Auger ObservatoryHadronNuclear physicsAtmosphere (unit)AugerTelescopeCascadeFunction (biology)GreisenDetectorAstrophysicsOpticsAtomic physicsThermodynamicsMaterials science

Abstract

fetched live from OpenAlex

Ultrahigh-energy cosmic rays are almost exclusively detected through extensive air showers, which they initiate upon interaction with the atmosphere. The longitudinal development of these air showers can be directly observed using fluorescence detector telescopes, such as those employed at the Pierre Auger Observatory or the Telescope Array. In this article, we discuss the properties of the Greisen function, which was initially derived as an approximate solution to the electromagnetic cascade equations, and its ability to describe the longitudinal shower profiles. We demonstrate that the Greisen function can be used to describe longitudinal air-shower profiles, even for hadronic air showers. Furthermore, we discuss the possibility to discriminate between hadrons and photons from the shape of air-shower profiles using the Greisen function.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.375
Teacher spread0.355 · 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 designSimulation or modeling
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
Published2023
Admission routes1
Has abstractyes

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