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Paper Citation Record · LEDGER

Classifying near-threshold enhancement using deep neural network

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2106.03453.

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

pith.paper-citation-record.v1
2106.03453 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:13:13.798422Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T15:39:34.735375Z

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 793b0268-2152-486a-b6cd-d52ef3db00bd · inbound

Analysis of hidden-charm pentaquarks as triangle singularities via deep learning cites this paper.

Analysis of hidden-charm pentaquarks as triangle singularities via deep learning Classifying near-threshold enhancement using deep neural network

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-12T15:39:34.752513Z

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.

source=arxiv_source observed=2026-08-12T15:39:34.324942Z digest=sha256:4b183d1838bb763a4955f73b99352e7ff76715c1c668c3a9193e42c4977d80d3

Observation a7bcd9df-b778-49a5-8bd7-b908be1be37e · inbound

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification cites this paper.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Classifying near-threshold enhancement using deep neural network

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-15T18:13:13.798422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:13:13.798422Z digest=sha256:994babb9447c6a989c4a3f7376212c52195a2abb7d4dc951e28b868e435ed820