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Paper Citation Record · LEDGER

Scientific machine learning for closure models in multiscale problems: a review

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2403.02913.

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

pith.paper-citation-record.v1
2403.02913 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:53:31.172306Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e2c02989-8b21-4fc8-9d8b-08b5d52a9d73 · inbound

Symbolic Regression of Data-Driven Reduced Order Model Closures for Under-Resolved, Convection-Dominated Flows cites this paper.

Symbolic Regression of Data-Driven Reduced Order Model Closures for Under-Resolved, Convection-Dominated Flows Scientific machine learning for closure models in multiscale problems: a review

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-08T21:53:31.172306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:53:31.172306Z digest=sha256:bc181f64ab47ed252513e70645c547a715ff8d5060a0e7e9cd5432fa227eed31

Observation 8066e7e7-7d03-46a6-bd2d-4fae9661b5bb · inbound

FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models cites this paper.

FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models Scientific machine learning for closure models in multiscale problems: a review

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T04:15:05.081651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:05.081651Z digest=sha256:b807acd768e6f2dfe13df5a711d399e07bd53d65b3260ea5b95948b8f091b249

Observation 0b5cd7c7-5d64-4fb7-ab12-6ab290d82cde · inbound

Modeling Partially Observed Nonlinear Dynamical Systems and Efficient Data Assimilation via Discrete-Time Conditional Gaussian Koopman Network cites this paper.

Modeling Partially Observed Nonlinear Dynamical Systems and Efficient Data Assimilation via Discrete-Time Conditional Gaussian Koopman Network Scientific machine learning for closure models in multiscale problems: a review

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:56.638646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:56.638646Z digest=sha256:e3a5f03526f5c4ca8014fac108ccd0804989425a053a323a9c8795fee61fc0bb

Observation 234fc238-48a8-4bd4-a610-b8f7d23f9e23 · inbound

Locally Adaptive Conformal Inference for Operator Models cites this paper.

Locally Adaptive Conformal Inference for Operator Models Scientific machine learning for closure models in multiscale problems: a review

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-06T13:15:43.370986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:15:43.370986Z digest=sha256:60342ff5d4fa2cf7441acf334e77fbb32e0e976929b53068090f5d67a7c4fc62

Observation a3c7947c-358a-4d1a-a65d-84bef18f678b · inbound

Multiscale Physics-Informed Neural Network for Complex Fluid Flows with Long-Range Dependencies cites this paper.

Multiscale Physics-Informed Neural Network for Complex Fluid Flows with Long-Range Dependencies Scientific machine learning for closure models in multiscale problems: a review

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:20:51.531523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T19:13:18.894727Z digest=sha256:0ec72f5d8973107fc6f89498fcbcdad906690ed236c66856db994420edb2557c

Observation 4a84ca8d-ee1f-4b8d-ad9f-2c4a04cc0f34 · inbound

A meshfree exterior calculus for generalizable and data-efficient learning of physics from point clouds cites this paper.

A meshfree exterior calculus for generalizable and data-efficient learning of physics from point clouds Scientific machine learning for closure models in multiscale problems: a review

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:11:15.883780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T02:09:01.875110Z digest=sha256:5250288a00eedbabd71eff2b99d5ba10870117f989f97ea625b56ead1857eb39

Observation dab05810-78a7-40b4-9a02-d55ff448c0ac · inbound

Wavelet Flow Matching for Multi-Scale Physics Emulation cites this paper.

Wavelet Flow Matching for Multi-Scale Physics Emulation Scientific machine learning for closure models in multiscale problems: a review

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-20T19:33:41.876401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T19:31:31.583420Z digest=sha256:0c7140289ed327dee7a17debf6d9d02c4f27c81d7b905c26a3199d301a570760

Observation 7cfcbba1-f103-4113-83d4-74986150d573 · inbound

Hybrid Neural Ordinary Differential Equations for Data-Efficient Polymerization Modeling with Incomplete Kinetics cites this paper.

Hybrid Neural Ordinary Differential Equations for Data-Efficient Polymerization Modeling with Incomplete Kinetics Scientific machine learning for closure models in multiscale problems: a review

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:56:15.819741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T16:01:16.642276Z digest=sha256:3747f78333a337abca4b5efaf7953284b4ab744ca705ac8a36f3948946cceeb7

Observation 5200b68a-9303-4503-8673-da1f70e03ed0 · inbound

Generalized Forcing Method: Generation of Diverse Data for Training Linear Transport PDE Closure Models cites this paper.

Generalized Forcing Method: Generation of Diverse Data for Training Linear Transport PDE Closure Models Scientific machine learning for closure models in multiscale problems: a review

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:26:54.542265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T03:49:50.921104Z digest=sha256:353c1aa087738d15873629f82899878d25c6d2c48b977e5a8cff9d3ab164b1d2

Observation 0b4bd3a4-b462-4249-a458-3179e2faa287 · inbound

Uncertainty-aware Multi-fidelity Closure via Conditional Normalizing Flows cites this paper.

Uncertainty-aware Multi-fidelity Closure via Conditional Normalizing Flows Scientific machine learning for closure models in multiscale problems: a review

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-06-29T13:43:28.758195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T13:39:13.750453Z digest=sha256:240395f68ec416f6ed79abed9b1a5347ffb42ec9d23826409182aebd950c2f1c

Observation f2039aa4-71d7-431a-8a6d-5197b6e0476e · inbound

Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics cites this paper.

Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics Scientific machine learning for closure models in multiscale problems: a review

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-06-27T11:00:50.703680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T10:55:15.050341Z digest=sha256:f171fd21d985c6f2840fac576563b0b32a77ea65121d46b088c952a98bf9982b

Observation 0c471c75-4758-4b80-a588-7dca0b860104 · inbound

Why Does the Future Branch? Identifiable Closure Tests for Stochastic Physical World Models cites this paper.

Why Does the Future Branch? Identifiable Closure Tests for Stochastic Physical World Models Scientific machine learning for closure models in multiscale problems: a review

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-05T00:42:28.448125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T00:42:28.448125Z digest=sha256:537d74ecd2ae3adf7ad0ba7db5fa38c3038239cd628331bdccdc0315a36e8826