Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in Connectomics
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2109.09649.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T05:33:22.880986Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T05:33:24.925018Z
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 4fd4dfc0-165a-4eb3-910a-0a966b7b656e · inbound
Uncertain but Useful: Leveraging CNN Training Variability into Data Augmentation cites this paper.
Uncertain but Useful: Leveraging CNN Training Variability into Data Augmentation Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in Connectomics
Reference 2022
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T05:33:25.035704Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.