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Paper Citation Record · LEDGER

Deep Convolutional Neural Networks for Pairwise Causality

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1701.00597.

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

pith.paper-citation-record.v1
1701.00597 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 2026-08-15T17:51:02.597528Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T18:50:04.600701Z

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 bbfd0f23-d57d-4c36-895d-7ccc2afb1136 · inbound

From Observations to Causations: A GNN-based Probabilistic Prediction Framework for Causal Discovery cites this paper.

From Observations to Causations: A GNN-based Probabilistic Prediction Framework for Causal Discovery Deep Convolutional Neural Networks for Pairwise Causality

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-15T17:51:02.597528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:51:02.597528Z digest=sha256:7cd87a119043085c3e4d0131f43fac2b91bccf4e2a7a10046c7601d7dbb03f15

Observation 5fb3a4c3-bb07-4397-8776-f4f33c6851b3 · inbound

Automated Residual Plot Assessment With the R Package autovi and the Shiny Application autovi.web cites this paper.

Automated Residual Plot Assessment With the R Package autovi and the Shiny Application autovi.web Deep Convolutional Neural Networks for Pairwise Causality

Reference 99

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T18:50:04.601969Z

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=2026-06-25T22:30:44.461821Z digest=sha256:a34b79679ce2621b768a9a24f3395a5fa489f3b71d07d5d1d5617e57f28936f0