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Paper Citation Record · LEDGER

Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.09454.

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

pith.paper-citation-record.v1
2312.09454 v2

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 2026-08-06T18:43:09.976398Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T20:16:10.854485Z

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 fe5fdcd6-da81-4448-a93b-78a19c5dc619 · inbound

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning cites this paper.

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T18:43:09.976398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:43:09.976398Z digest=sha256:40969fa33a677bf8df91dd27ed96c39ab368a193647ae378f2ead5c23f89822d

Observation 8a17313d-bded-4102-81cc-451f3d30e227 · inbound

Is the Last Layer Sufficient for Uncertainty Quantification? cites this paper.

Is the Last Layer Sufficient for Uncertainty Quantification? Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-01T20:16:10.856486Z

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=2026-06-28T21:33:57.947910Z digest=sha256:824f70697736997201e7dd220bebd80dda47f93dc6a2ef99e2b74ea8d5c67685