Paper Citation Record · LEDGER

Application of Deep Neural Networks to Event Type Classification in IceCube

As of 16 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 1 inbound Pith citation observation for arXiv:1908.08763.

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

pith.paper-citation-record.v1
1908.08763 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:32:59.450288Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:26:31.202224Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-12T18:16:22.223912Z

Reference resolution

11 of 11 outbound references displayed

verified exact0
verified fuzzy1
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9e716ba0-adcd-4ebe-b0ae-5fa5364d61cb · outbound

This paper cites write newline.

Application of Deep Neural Networks to Event Type Classification in IceCube write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T11:32:59.392596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf5c502e-4953-4091-8620-201295dd59a9 · outbound

This paper cites Going Deeper with Convolutions.

Application of Deep Neural Networks to Event Type Classification in IceCube Going Deeper with Convolutions

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T11:32:59.399680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 393a84f4-67cb-492f-8d8b-8b86bb75f744 · outbound

This paper cites Rethinking the Inception Architecture for Computer Vision.

Application of Deep Neural Networks to Event Type Classification in IceCube Rethinking the Inception Architecture for Computer Vision

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T11:32:59.405319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0c0ab9c-070f-415f-8efe-275426d6225a · outbound

This paper cites Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning.

Application of Deep Neural Networks to Event Type Classification in IceCube Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T11:32:59.411803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b2d222e-918f-42c1-8d9f-80fe154cb29c · outbound

This paper cites an unresolved cited work.

Application of Deep Neural Networks to Event Type Classification in IceCube Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:32:59.683054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9f507d6d-6542-4b75-91a5-54282241d8a5 · outbound

This paper cites Beringer et al.

Application of Deep Neural Networks to Event Type Classification in IceCube Beringer et al

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:32:59.662945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 81c64792-f11f-4a02-a6cb-c1fd139c7e71 · outbound

This paper cites an unresolved cited work.

Application of Deep Neural Networks to Event Type Classification in IceCube Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:32:59.643933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 450cda78-306d-46df-b3aa-f707f5572de4 · outbound

This paper cites an unresolved cited work.

Application of Deep Neural Networks to Event Type Classification in IceCube Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:32:59.620564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d918f189-3b27-4a2a-ba6d-e765945d513a · outbound

This paper cites an unresolved cited work.

Application of Deep Neural Networks to Event Type Classification in IceCube Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:32:59.601891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bf64ebef-615a-4d0b-a835-796138a07548 · outbound

This paper cites an unresolved cited work.

Application of Deep Neural Networks to Event Type Classification in IceCube Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:32:59.582815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4a459bff-1320-401c-8c00-166772cef73e · outbound

This paper cites an unresolved cited work.

Application of Deep Neural Networks to Event Type Classification in IceCube Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:32:59.563208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation 26e9e14d-006d-4857-88f8-92c6257edbcf · inbound

flashcurve: A machine-learning approach for the simple and fast generation of adaptive-binning light curves with Fermi-LAT data cites this paper.

flashcurve: A machine-learning approach for the simple and fast generation of adaptive-binning light curves with Fermi-LAT data Application of Deep Neural Networks to Event Type Classification in IceCube

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-12T17:26:31.377516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.