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Paper Citation Record · LEDGER

Navigating protein landscapes with a machine-learned transferable coarse-grained model

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.18278.

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

pith.paper-citation-record.v1
2310.18278 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:16:02.001124Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T18:50:04.643304Z

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 0289db66-4899-4e05-b71b-afdfe3a96f48 · inbound

Graph-Coarsening for Machine Learning Coarse-grained Molecular Dynamics cites this paper.

Graph-Coarsening for Machine Learning Coarse-grained Molecular Dynamics Navigating protein landscapes with a machine-learned transferable coarse-grained model

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T15:16:02.001124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:16:02.001124Z digest=sha256:8ee419b16143bc3df675c566b4ce4af7b92e3388cfc686400e190bf5be005175

Observation 5c2dfde9-9a99-4424-84c6-8f50098a2d0f · inbound

ConSolv: Solvent-Conditional Machine Learning Implicit Solvent Potential cites this paper.

ConSolv: Solvent-Conditional Machine Learning Implicit Solvent Potential Navigating protein landscapes with a machine-learned transferable coarse-grained model

Reference 276

Resolution
verified exact
arxiv_id, observed 2026-07-04T18:50:04.644812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-25T22:29:00.093118Z digest=sha256:0c673a8979084b7b7a7caf740a808c3467e16e5b2bb6705ead6996afbb8ec139