Paper Citation Record · LEDGER

Machine and Deep Learning Applications in Particle Physics

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1912.08245.

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

pith.paper-citation-record.v1
1912.08245 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:40:35.489786Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T18:48:08.189709Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 28f26e08-5223-49f0-b4e1-42bfa1956eab · inbound

Systematically Constructing the Likelihood for Boosted $H\to gg$ Decays cites this paper.

Systematically Constructing the Likelihood for Boosted $H\to gg$ Decays Machine and Deep Learning Applications in Particle Physics

Reference 10

Resolution: malformed identifier; no resolver link, observed 2026-08-12T19:45:07.806854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47a73892-6719-4ef5-99cd-277cc7ad2c7b · inbound

Machine Learning Insights into Quark-Antiquark Interactions: Probing Field Distributions and String Tension in QCD cites this paper.

Machine Learning Insights into Quark-Antiquark Interactions: Probing Field Distributions and String Tension in QCD Machine and Deep Learning Applications in Particle Physics

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T14:51:39.670672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 899fe640-2e4f-4636-994a-b6fcc6e087cc · inbound

A Step Toward Interpretability: Smearing the Likelihood cites this paper.

A Step Toward Interpretability: Smearing the Likelihood Machine and Deep Learning Applications in Particle Physics

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T20:44:15.480878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad582e38-272c-403a-a011-1027911fb630 · inbound

Factorization for Collider Dataspace Correlators cites this paper.

Factorization for Collider Dataspace Correlators Machine and Deep Learning Applications in Particle Physics

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:35.489786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5827fb3-64be-497f-a7e9-f4d1208d5394 · inbound

Shedding Light on Dark Matter at the LHC with Machine Learning cites this paper.

Shedding Light on Dark Matter at the LHC with Machine Learning Machine and Deep Learning Applications in Particle Physics

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T16:19:44.863278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a4b11a1-9781-45e7-8f80-cd00f08066b1 · inbound

Probing Proton Structure via Physics-Guided Neural Networks in Holographic QCD cites this paper.

Probing Proton Structure via Physics-Guided Neural Networks in Holographic QCD Machine and Deep Learning Applications in Particle Physics

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:48:08.191120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b8f0fbc6-4d67-4b45-93bb-2fa31aaa216d · inbound

Simplex Demixing: Disentangling Multiple Light-Flavor Jets at Colliders cites this paper.

Simplex Demixing: Disentangling Multiple Light-Flavor Jets at Colliders Machine and Deep Learning Applications in Particle Physics

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-31T05:57:07.287391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.