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Paper Citation Record · LEDGER

Materials Property Prediction with Uncertainty Quantification: A Benchmark Study

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.02235.

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

pith.paper-citation-record.v1
2211.02235 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 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T07:08:16.449041Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T07:11:12.802619Z

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 96950aec-869b-4604-8f2b-2b99647a8f69 · inbound

Scale-Dependent Input Representation and Confidence Estimation for LLMs in Materials Property Prediction cites this paper.

Scale-Dependent Input Representation and Confidence Estimation for LLMs in Materials Property Prediction Materials Property Prediction with Uncertainty Quantification: A Benchmark Study

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T11:01:31.600919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-07T16:03:26.733022Z digest=sha256:1698ed03546befc8c9e024506d05a7818484d1dd7e393551e7de7ea876fb0800

Observation 813db389-47c9-4992-a25c-3b36e56b46a6 · inbound

Do Deep Ensembles Actually Capture Uncertainty in Graph Neural Networks? cites this paper.

Do Deep Ensembles Actually Capture Uncertainty in Graph Neural Networks? Materials Property Prediction with Uncertainty Quantification: A Benchmark Study

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-22T07:11:12.805911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-22T07:08:16.449041Z digest=sha256:987ac4aa9e95be51c178d0099db0c139ed1ece09e93e7bd552f85d0cc041f62f