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Paper Citation Record · LEDGER

Interpretable deep learning for nuclear deformation in heavy ion collisions

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1906.06429.

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

pith.paper-citation-record.v1
1906.06429 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:33:43.437490Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T22:33:43.498468Z

Reference resolution

0 of 0 outbound references displayed

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  • 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 b52d98bf-b8f7-476a-9ce4-f23f01712a78 · inbound

Validation and extrapolation of atomic mass with physics-informed fully connected neural network cites this paper.

Validation and extrapolation of atomic mass with physics-informed fully connected neural network Interpretable deep learning for nuclear deformation in heavy ion collisions

Reference 89

Resolution
verified exact
local_arxiv, observed 2026-08-10T22:33:43.505787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:33:43.437490Z digest=sha256:4608991d6b5e3bcc49a4005bb040c9394b08dffe68e67ca4badfe68a2cf43a7e

Observation 9efa732e-06a8-4827-8d07-4a8c7c752308 · inbound

A deep learning approach for predicting multiple observables in Au+Au collisions at RHIC cites this paper.

A deep learning approach for predicting multiple observables in Au+Au collisions at RHIC Interpretable deep learning for nuclear deformation in heavy ion collisions

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-03T21:59:53.481434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:59:53.481434Z digest=sha256:9e3546af004a23ba67da118a2b4cd67881b9f8ca98a46244ab62bdbb4e788a86