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Paper Citation Record · LEDGER

PySensors: A Python Package for Sparse Sensor Placement

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2102.13476.

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

pith.paper-citation-record.v1
2102.13476 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:31:52.460021Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:39:57.954457Z

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 1bcad4d9-3644-4162-8cad-9cdc4468fe49 · inbound

Sparse Sensor Allocation for Inverse Problems of Detecting Sparse Leaking Emission Sources cites this paper.

Sparse Sensor Allocation for Inverse Problems of Detecting Sparse Leaking Emission Sources PySensors: A Python Package for Sparse Sensor Placement

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T16:31:52.460021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:31:52.460021Z digest=sha256:09691445e4106da4920fcdfb4a34f2c0cb95290da738e5475597cd6648589172

Observation 78a6e789-6b7c-4ea8-8471-6e50de1d2151 · inbound

Low-Cost High-Order Singular Value Decomposition for Tensor-Based Reconstruction from Sparse Sensor Measurements: Urban Flow and Air-Quality Applications cites this paper.

Low-Cost High-Order Singular Value Decomposition for Tensor-Based Reconstruction from Sparse Sensor Measurements: Urban Flow and Air-Quality Applications PySensors: A Python Package for Sparse Sensor Placement

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:39:57.956046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T00:20:48.560778Z digest=sha256:b773fb163892670cbc0eb241754faa8adad7740bd32329156d086ecfcd53c5eb

Observation f1cff01f-b956-45a3-b20b-578c40340f04 · inbound

Origins and mitigation of double descent in reduced order modeling cites this paper.

Origins and mitigation of double descent in reduced order modeling PySensors: A Python Package for Sparse Sensor Placement

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-01T16:33:04.885199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T16:33:04.885199Z digest=sha256:3376cdf36377a3d315d9015ff1bdaa14af47b3ea1cee3dedeffd9f7b3901e671