Paper Citation Record · LEDGER

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles

As of 5 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2508.13933.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.13933 v5

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measured 24 of 24 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-07-11T11:50:26.030339Z

measured 24 of 24 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

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measured 0 of 1 external citation measurements

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Reference resolution

24 of 24 outbound references displayed

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Outbound references

Observation c4f6c0c8-3e83-46cf-a3d6-bdc94a8f424d · outbound

This paper cites Depth of Maximum of Air-Shower Profiles at the Pierre Auger Observatory: Measurements at Energies above 10^17.8 eV.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Depth of Maximum of Air-Shower Profiles at the Pierre Auger Observatory: Measurements at Energies above 10^17.8 eV

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.607233Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 81d02c00-7bd8-4916-9cb8-acc2ee569339 · outbound

This paper cites Aab, et al., Features of the Energy Spectrum of Cosmic Rays above 2.5×10 18 eV Using the Pierre Auger Observatory, Phys.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Aab, et al., Features of the Energy Spectrum of Cosmic Rays above 2.5×10 18 eV Using the Pierre Auger Observatory, Phys

Reference 2

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.545390Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5a58c866-bb00-4b91-989e-dc7fe98b323e · outbound

This paper cites Pierog, I.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Pierog, I

Reference 3

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.540686Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9a94d356-fe29-45c5-836d-eb35634d0282 · outbound

This paper cites Riehn, R.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Riehn, R

Reference 4

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.549399Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation de54a0b5-0e26-4116-bb66-25b91cbd8225 · outbound

This paper cites Coleman, J.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Coleman, J

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T22:22:51.559953Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 54432351-1149-4836-8266-9030b25092c7 · outbound

This paper cites Measurements of the Cosmic Ray Composition with Air Shower Experiments.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Measurements of the Cosmic Ray Composition with Air Shower Experiments

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.590024Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8151cbdd-bd93-4592-9129-c99795d89004 · outbound

This paper cites an unresolved cited work.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Unresolved cited work

Reference 7

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.578763Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a159d650-2d9c-46f1-b861-02ef40f13e70 · outbound

This paper cites Comparison between methods for the determination of the primary cosmic ray mass composition from the longitudinal profile of atmospheric cascades.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Comparison between methods for the determination of the primary cosmic ray mass composition from the longitudinal profile of atmospheric cascades

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.597266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ae3f6631-110e-4f3b-a505-b9779d062fc3 · outbound

This paper cites Riggi, R.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Riggi, R

Reference 9

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.610024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ee93b4dd-d758-44b2-a8b1-b5ca1b260826 · outbound

This paper cites Andringa, R.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Andringa, R

Reference 10

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.610772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c03cd3f2-c185-491f-8c5d-65d7f96e02c8 · outbound

This paper cites Measurement of the average shape of longitudinal profiles of cosmic-ray air showers at the Pierre Auger Observatory.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Measurement of the average shape of longitudinal profiles of cosmic-ray air showers at the Pierre Auger Observatory

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.602637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 85cc9d18-f714-4eb0-b778-0d11292acb62 · outbound

This paper cites Abdul Halim, et al., Inference of the Mass Composition of Cosmic Rays with Energies from 1018.5 to 1020 eV Using the Pierre Auger Observatory and Deep Learning, Phys.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Abdul Halim, et al., Inference of the Mass Composition of Cosmic Rays with Energies from 1018.5 to 1020 eV Using the Pierre Auger Observatory and Deep Learning, Phys

Reference 12

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.568372Z

Source-reported events for the cited work

correction dated 2025-01-13. Source: crossref record 10.1103/physrevlett.134.021001->10.1103/physrevlett.134.021001:correction, observed 2026-07-11T03:08:16.112457+00:00. This notice travels one citation hop only.

Observation 29348258-c048-42d1-b1e2-9c1281ac2b40 · outbound

This paper cites One-dimensional Hybrid Approach to Extensive Air Shower Simulation.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles One-dimensional Hybrid Approach to Extensive Air Shower Simulation

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.665670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 61be9fb4-d874-4c4c-96ba-36c9ea2100d6 · outbound

This paper cites First Results of Fast One-dimensional Hybrid Simulation of EAS Using CONEX.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles First Results of Fast One-dimensional Hybrid Simulation of EAS Using CONEX

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.641937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7566939f-3305-4f9e-9b40-c4f12ded3747 · outbound

This paper cites Inferences on Mass Composition and Tests of Hadronic Interactions from 0.3 to 100 EeV using the water-Cherenkov Detectors of the Pierre Auger Observatory.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Inferences on Mass Composition and Tests of Hadronic Interactions from 0.3 to 100 EeV using the water-Cherenkov Detectors of the Pierre Auger Observatory

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.585911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a27dd303-0638-4aaf-8ec2-04afb5249b1b · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.646195Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 574204dd-0a31-4723-9ee7-6167b7e48c90 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Deep Residual Learning for Image Recognition

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T22:22:51.615016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2ca927ff-7b6f-435f-aba3-1fa20b615c7b · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.650583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8f079290-6c3e-40ca-928e-b0f6f3bb6951 · outbound

This paper cites URLhttps://doi.org/10.5281/zenodo.10488964.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles URLhttps://doi.org/10.5281/zenodo.10488964

Reference 19

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.606961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dfa00a57-8cc7-4f02-8512-e0667ccea477 · outbound

This paper cites Flaggs, A.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Flaggs, A

Reference 20

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.619514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d2ec23fa-d63d-4e66-bc90-e0e5ad2a8f04 · outbound

This paper cites Measurement and Interpretation of UHECR Mass Composition at the Pierre Auger Observatory.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Measurement and Interpretation of UHECR Mass Composition at the Pierre Auger Observatory

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:22:51.660842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 99df587b-3bf1-41aa-917d-3808a15526ba · outbound

This paper cites The Fluorescence Detector of the Pierre Auger Observatory.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles The Fluorescence Detector of the Pierre Auger Observatory

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.554516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1123f769-0bc5-428a-8637-053188caf0ef · outbound

This paper cites Kawai, et al., Telescope array experiment, Nucl.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles Kawai, et al., Telescope array experiment, Nucl

Reference 23

Resolution: verified exact; doi, observed 2026-05-18T22:22:51.549147Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 53957de7-e2d8-46f5-be56-c4096db1f4d9 · outbound

This paper cites The Global Cosmic Ray Observatory -- Challenging next-generation multi-messenger astronomy with interdisciplinary research.

Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles The Global Cosmic Ray Observatory -- Challenging next-generation multi-messenger astronomy with interdisciplinary research

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:22:51.654363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

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