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Paper Citation Record · LEDGER

Quantum ensembles of quantum classifiers

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1704.02146.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1704.02146 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:55:32.581077Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T18:16:30.548575Z

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 2ba3bc26-df94-45bf-b148-241316f607bd · inbound

Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning cites this paper.

Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning Quantum ensembles of quantum classifiers

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:49:21.228516Z

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.

source=pdf_text observed=2026-08-06T15:49:16.993588Z digest=sha256:9d920ca42be1e0bc82ada2f59312858036c81b23ca41a6c61a598edb7344fe50

Observation 1fe422f5-853f-4006-b1b4-515ac1ba846d · inbound

How Much Reconstruction Does Quantum Machine Learning Need? Late Fusion of Independently Trained Quantum Subcircuits cites this paper.

How Much Reconstruction Does Quantum Machine Learning Need? Late Fusion of Independently Trained Quantum Subcircuits Quantum ensembles of quantum classifiers

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T05:55:32.581077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T05:55:32.581077Z digest=sha256:dfc2e51e156b45b7095b6b54d86c58d67fcc6b67d4d3c9736d590ddaef4cc1a7