Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Test & Evaluation Best Practices for Machine Learning-Enabled Systems
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2310.06800.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T05:05:10.626842Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T02:07:33.271701Z
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 292c08e0-3774-4f84-9342-1ed0b50cbde4 · inbound
Approach Towards Semi-Automated Certification for Low Criticality ML-Enabled Airborne Applications cites this paper.
Approach Towards Semi-Automated Certification for Low Criticality ML-Enabled Airborne Applications Test & Evaluation Best Practices for Machine Learning-Enabled Systems
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T05:05:10.626842Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c06a4ab-7d1a-448f-b698-d7b15d856b60 · inbound
From Tea Leaves to System Maps: A Survey and Framework on Context-aware Machine Learning Monitoring cites this paper.
From Tea Leaves to System Maps: A Survey and Framework on Context-aware Machine Learning Monitoring Test & Evaluation Best Practices for Machine Learning-Enabled Systems
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:21:56.026567Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7ff8246-6aca-4a75-a1ad-594b2a8564d1 · inbound
Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting cites this paper.
Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting Test & Evaluation Best Practices for Machine Learning-Enabled Systems
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T02:07:33.273535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.