Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Interpretable machine learning in Physics
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2203.08021.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T20:44:15.555129Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T00:01:14.850248Z
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 7793ecc7-85a5-4980-ae4d-71456e140c00 · inbound
A Step Toward Interpretability: Smearing the Likelihood cites this paper.
A Step Toward Interpretability: Smearing the Likelihood Interpretable machine learning in Physics
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:44:15.555129Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dec8b18a-e073-4cec-b802-1f7f6b25b8fc · inbound
Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane cites this paper.
Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane Interpretable machine learning in Physics
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T00:01:14.852924Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 9d80da26-5cee-4f06-990f-5cc7792b0746 · inbound
Probing dark matter through charged Higgs pair production at future multi-TeV muon colliders: A machine-learning analysis cites this paper.
Probing dark matter through charged Higgs pair production at future multi-TeV muon colliders: A machine-learning analysis Interpretable machine learning in Physics
Reference 75
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:47:53.289827Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.