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Paper Citation Record · LEDGER

Quantile Regression using Random Forest Proximities

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.02355.

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

pith.paper-citation-record.v1
2408.02355 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:32:07.471901Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T15:11:05.043491Z

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 42cd6cb3-11f9-4226-8999-24ad8fc3d26a · inbound

Dual Interpretation of Machine Learning Forecasts cites this paper.

Dual Interpretation of Machine Learning Forecasts Quantile Regression using Random Forest Proximities

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-11T13:32:07.471901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:32:07.471901Z digest=sha256:05e3f6f5bb3eb674651b110aafec05111042f73c0550677cd7c17f741950c2a9

Observation 61a33f51-f547-4c36-8d66-b966fe0a15f3 · inbound

Supervised Similarity for High-Yield Corporate Bonds with Quantum Cognition Machine Learning cites this paper.

Supervised Similarity for High-Yield Corporate Bonds with Quantum Cognition Machine Learning Quantile Regression using Random Forest Proximities

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-09T15:11:05.046975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-09T15:11:04.944972Z digest=sha256:08527ce2912c81019118e323db292b8ed5bbdcf4357c5489c952c8933890fc73