Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Unsupervised quantum machine learning for fraud detection
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2208.01203.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:03:32.399112Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T14:50:04.518945Z
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 31094bf8-7193-48dc-bf50-6eb31a9dddf2 · inbound
Comparative Analysis of QNN Architectures for Wind Power Prediction: Feature Maps and Ansatz Configurations cites this paper.
Comparative Analysis of QNN Architectures for Wind Power Prediction: Feature Maps and Ansatz Configurations Unsupervised quantum machine learning for fraud detection
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:03:32.399112Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4b49106f-a016-47be-93af-b686650d4f76 · inbound
Quantum Neural Networks for Wind Energy Forecasting: A Comparative Study of Performance and Scalability with Classical Models cites this paper.
Quantum Neural Networks for Wind Energy Forecasting: A Comparative Study of Performance and Scalability with Classical Models Unsupervised quantum machine learning for fraud detection
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:25.081524Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f011ea28-c0ab-4490-8e2f-d04d61325b9d · inbound
A Mixture-of-Experts Framework for Practical Hybrid-Quantum Models in Credit Card Fraud Detection cites this paper.
A Mixture-of-Experts Framework for Practical Hybrid-Quantum Models in Credit Card Fraud Detection Unsupervised quantum machine learning for fraud detection
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T14:50:04.521276Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.