Paper Citation Record · LEDGER

Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1910.09457.

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

pith.paper-citation-record.v1
1910.09457 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:29:58.829122Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T06:41:32.964719Z

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 54ccc2d4-a910-4e46-b124-b41591948a7d · inbound

Performance Prediction for Large Systems via Text-to-Text Regression cites this paper.

Performance Prediction for Large Systems via Text-to-Text Regression Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:29:58.829122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52ae1f49-8be5-4f7f-b2f9-5a2f143394ab · inbound

Uncertainty Quantification for Surface Ozone Emulators using Deep Learning cites this paper.

Uncertainty Quantification for Surface Ozone Emulators using Deep Learning Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T23:45:27.419404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fb586dc-656d-4733-9569-90b3ced617e0 · inbound

Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation cites this paper.

Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:32.969664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 13d4ed86-32a5-4a6b-9c60-5fa27a5cac33 · inbound

Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation cites this paper.

Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

Reference 105

Resolution: unresolved; no resolver link, observed 2026-08-02T14:26:27.391498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.