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Paper Citation Record · LEDGER

Online Active Learning for Soft Sensor Development using Semi-Supervised Autoencoders

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2212.13067.

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

pith.paper-citation-record.v1
2212.13067 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T01:53:55.273340Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:18:54.960263Z

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 c9f13ad6-d96e-4ef2-9dc7-831ad67509a8 · inbound

QueryMarket: Cost-Aware Online Active Learning in Data Markets cites this paper.

QueryMarket: Cost-Aware Online Active Learning in Data Markets Online Active Learning for Soft Sensor Development using Semi-Supervised Autoencoders

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-03T19:18:54.961877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T01:53:55.273340Z digest=sha256:38fe2d0a6340df2d9d3d92761b7957d226d142b22c6c3b37a67a7c8bd6a0f23e