Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enhancing Computational Fluid Dynamics with Machine Learning
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2110.02085.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T05:29:46.658313Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T03:11:19.218047Z
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 bb3a4ccf-025e-4b0d-a2f2-06d171c96776 · inbound
PAL -- Parallel active learning for machine-learned potentials cites this paper.
PAL -- Parallel active learning for machine-learned potentials Enhancing Computational Fluid Dynamics with Machine Learning
Reference 66
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:29:46.658313Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 58c4b1b0-e030-430d-aa2f-cef97c91962d · inbound
Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics cites this paper.
Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Enhancing Computational Fluid Dynamics with Machine Learning
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:47:18.043513Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1146f807-e3df-474a-99cb-16d5b80f6e00 · inbound
Enabling Structure-Only Initialization and Out-of-Distribution Generalization in GNN-based Molecular Dynamics Simulators cites this paper.
Enabling Structure-Only Initialization and Out-of-Distribution Generalization in GNN-based Molecular Dynamics Simulators Enhancing Computational Fluid Dynamics with Machine Learning
Reference 168
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T03:11:19.219972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.