Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
CarbNN: A Novel Active Transfer Learning Neural Network To Build De Novo Metal Organic Frameworks (MOFs) for Carbon Capture
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.16158.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T10:10:02.473740Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
2
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation e237e44c-d6fb-4274-8c0d-04b9588b8a42 · inbound
MatCreatioNN: Machine learning-guided computational discovery of photocatalysts for environmental applications cites this paper.
MatCreatioNN: Machine learning-guided computational discovery of photocatalysts for environmental applications CarbNN: A Novel Active Transfer Learning Neural Network To Build De Novo Metal Organic Frameworks (MOFs) for Carbon Capture
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-01T10:13:36.066788Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b9db000d-e686-473a-9d7d-814937c29464 · inbound
Machine Learning for Designing Undesignable Metal-Organic Frameworks cites this paper.
Machine Learning for Designing Undesignable Metal-Organic Frameworks CarbNN: A Novel Active Transfer Learning Neural Network To Build De Novo Metal Organic Frameworks (MOFs) for Carbon Capture
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T08:44:00.298051Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.