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Paper Citation Record · LEDGER

Explainability of Machine Learning Models under Missing Data

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.00411.

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

pith.paper-citation-record.v1
2407.00411 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 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T18:01:09.829489Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T05:40:57.657790Z

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 9056c361-4efe-458e-89d2-4a9634e86a2d · inbound

Evaluating Counterfactual Explanation Methods on Incomplete Inputs cites this paper.

Evaluating Counterfactual Explanation Methods on Incomplete Inputs Explainability of Machine Learning Models under Missing Data

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:40:57.661981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T18:01:09.829489Z digest=sha256:fa2707b1cc2af336e5ad7a63de692bd11fc1d5d19e192ba6998ef6e23b4972b5

Observation e0b6b967-7908-4041-8ac0-185f126ed02e · inbound

Improving post-operative discharge destination prediction of geriatric patients with generative data augmentation cites this paper.

Improving post-operative discharge destination prediction of geriatric patients with generative data augmentation Explainability of Machine Learning Models under Missing Data

Reference 33

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T05:51:10.551545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T05:43:25.635657Z digest=sha256:221432064d32be71fbb4f3c9eccea81696e036871cae3ddd78d608abdcc600ac