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Paper Citation Record · LEDGER

Uncertainty Quantification on Clinical Trial Outcome Prediction

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.03482.

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

pith.paper-citation-record.v1
2401.03482 v3

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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:03:41.954751Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T20:33:25.821557Z

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 59ca6fe5-3bcf-4264-a310-7e102309bd6f · inbound

Quantum-inspired Reinforcement Learning for Synthesizable Drug Design cites this paper.

Quantum-inspired Reinforcement Learning for Synthesizable Drug Design Uncertainty Quantification on Clinical Trial Outcome Prediction

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:33:25.824103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-23T20:30:04.338912Z digest=sha256:dff5a2ade3049065a132aa87c2b1392ead76bd87465ae2a97e808d637f752472

Observation a2a4ae00-05b1-439e-bdaa-2f1578d4f2de · inbound

FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation cites this paper.

FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation Uncertainty Quantification on Clinical Trial Outcome Prediction

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T15:03:41.954751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:03:41.954751Z digest=sha256:4e642c34263101f699999b71942954abf8e1ac4a6b402d16804966aade3ee24c