Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Benchmarking deep learning models for bearing fault diagnosis using the CWRU dataset: A multi-label approach
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2407.14625.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-10T16:05:28.404367Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T16:07:20.377973Z
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 748c1908-1723-4dc9-be8b-6401bbe4179e · inbound
Nigeria Machinery: A Low-Resource Industrial Dataset with a Domain-Grounded Reasoning Layer cites this paper.
Nigeria Machinery: A Low-Resource Industrial Dataset with a Domain-Grounded Reasoning Layer Benchmarking deep learning models for bearing fault diagnosis using the CWRU dataset: A multi-label approach
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T16:07:20.379474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.