Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On the impact of selected modern deep-learning techniques to the performance and celerity of classification models in an experimental high-energy physics use case
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2002.01427.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T21:24:07.357584Z
A source-named dated measurement, never combined with another source.
Source: cited_works
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 922e37a1-f09a-442e-849c-d0927e56ac68 · inbound
From Qubits to Couplings: A Hybrid Quantum Machine Learning Framework for LHC Physics cites this paper.
From Qubits to Couplings: A Hybrid Quantum Machine Learning Framework for LHC Physics On the impact of selected modern deep-learning techniques to the performance and celerity of classification models in an experimental high-energy physics use case
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T21:24:07.357584Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49abf2d2-2250-4ad2-9c58-3014a41a5839 · inbound
Probing new physics in the Boosted $HH \to b\bar{b}\gamma\gamma$ channel at the LHC cites this paper.
Probing new physics in the Boosted $HH \to b\bar{b}\gamma\gamma$ channel at the LHC On the impact of selected modern deep-learning techniques to the performance and celerity of classification models in an experimental high-energy physics use case
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T15:18:46.231390Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.