Paper Citation Record · LEDGER

What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1904.02826.

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

pith.paper-citation-record.v1
1904.02826 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:16:51.532221Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:39:39.701440Z

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 a14b9c49-8e8b-44d8-a6cc-fcacb7d05a5f · inbound

Invariant Image Reparameterisation: Bridging Symbolic and Numerical Methods for Identifiability Analysis, Model Reduction, and Prediction cites this paper.

Invariant Image Reparameterisation: Bridging Symbolic and Numerical Methods for Identifiability Analysis, Model Reduction, and Prediction What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:25:23.476443Z

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.

Observation 8fa2e728-c8cf-4bc0-9a5e-d6f981179943 · inbound

Invariant Image Reparameterisation: Bridging Symbolic and Numerical Methods for Identifiability Analysis, Model Reduction, and Prediction cites this paper.

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-08T21:16:51.532221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16f17f99-dbdb-4e4a-9d08-1a66e3143ce7 · inbound

Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series cites this paper.

Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T13:55:48.504499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a317fee4-7f42-4ffd-8f5a-dccfa7212fb2 · inbound

Constructing g-computation estimators: two case studies in selection bias cites this paper.

Constructing g-computation estimators: two case studies in selection bias What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T11:11:23.955854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0cf5778-55b8-4cf7-99b9-962187df851b · inbound

Unifying Statistical and Mathematical Modeling Through a Causal Inference Lens cites this paper.

Unifying Statistical and Mathematical Modeling Through a Causal Inference Lens What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-04T00:23:06.325765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a93316b-70cc-4c3f-8282-f2d4cc474f20 · inbound

From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models cites this paper.

From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems

Reference 51

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:47:30.244701Z

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.

Observation f07c9da7-8590-4cc6-9613-685521286e70 · inbound

From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models cites this paper.

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-02T12:05:38.756853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07c7d8b8-29fe-4f13-9b3c-898e394b6fc3 · inbound

Two Layers of Instability in Causal Estimation cites this paper.

Two Layers of Instability in Causal Estimation What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:39:39.713943Z

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.

Observation 667dde83-87e4-462d-b9b0-16a4339721b5 · inbound

Two Layers of Instability in Causal Estimation cites this paper.

Two Layers of Instability in Causal Estimation What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-12T13:07:53.002127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.