Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1905.04223.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T00:48:45.731738Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-20T03:43:02.094425Z
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 d6dcfbd0-28d4-43a6-88e3-da88ebbb1278 · inbound
Bridging the Disciplinary Gap in Explainable AI: From Abstract Desiderata to Concrete Tasks cites this paper.
Bridging the Disciplinary Gap in Explainable AI: From Abstract Desiderata to Concrete Tasks Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T03:43:02.097844Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d9bd4af6-0f14-440b-a67f-32f6baa3dd17 · inbound
Towards Trustworthy Embodied Intelligence: A Systems Framework and Graded Trustworthiness Levels cites this paper.
Towards Trustworthy Embodied Intelligence: A Systems Framework and Graded Trustworthiness Levels Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges
Reference 81
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:48:45.731738Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.