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Paper Citation Record · LEDGER

Non-Stationary Spatial Modeling

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2212.08043.

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

pith.paper-citation-record.v1
2212.08043 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 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:03:33.864972Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T15:03:33.931514Z

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 002d308c-2d57-40c8-854d-aba78c8ba802 · inbound

Bayesian "Deep" Process Convolutions: An Application in Cosmology cites this paper.

Bayesian "Deep" Process Convolutions: An Application in Cosmology Non-Stationary Spatial Modeling

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-12T15:03:33.997357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T15:03:33.864972Z digest=sha256:350e161bf2bec22d4e45a2c914d85fb762b1dd88545e976bcc8ae2313bbbbbf9

Observation 2714eef2-f92f-4ad9-a960-276706637c4c · inbound

gp2Scale: A Class of Compactly Supported Non-Stationary Kernels and Distributed Computing for Exact Gaussian Processes on 10 Million Data Points cites this paper.

gp2Scale: A Class of Compactly Supported Non-Stationary Kernels and Distributed Computing for Exact Gaussian Processes on 10 Million Data Points Non-Stationary Spatial Modeling

Reference 2013

Resolution
unresolved
no resolver link, observed 2026-08-03T18:17:43.897554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:17:43.897554Z digest=sha256:3c16658966e94ec064f5350d2c3f98f76e1a1acbdbdca29de6b9cd6baf9bfc10