Paper Citation Record · LEDGER

Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion

As of 21 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 1 inbound Pith citation observation for arXiv:2507.08426.

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

pith.paper-citation-record.v1
2507.08426 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:26:49.374647Z

measured 8 of 8 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-07T14:13:10.563497Z

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

7 of 7 outbound references displayed

verified exact2
verified fuzzy0
unresolved3
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 44adbbf4-879f-41fe-8aa9-97194ea3317f · outbound

This paper cites an unresolved cited work.

Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion Unresolved cited work

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-06T18:26:49.374647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c67a9296-ab54-4879-839c-3b09f8e6bc79 · outbound

This paper cites an unresolved cited work.

Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion Unresolved cited work

Reference 149

Resolution: malformed identifier; no resolver link, observed 2026-08-06T18:26:49.369727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7621f5c7-3a1a-4317-8d63-cf18e7dfd5cf · outbound

This paper cites an unresolved cited work.

Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion Unresolved cited work

Reference 531

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T18:26:49.646520Z

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.

Observation ef713f66-a12a-4543-8bdf-1bb10a02c0e5 · outbound

This paper cites an unresolved cited work.

Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion Unresolved cited work

Reference 925

Resolution: unresolved; no resolver link, observed 2026-08-06T18:26:49.352665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99b36e72-44c2-4ab1-8942-2b59182bf693 · outbound

This paper cites an unresolved cited work.

Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion Unresolved cited work

Reference 1154

Resolution: verified exact; doi, observed 2026-08-06T18:26:49.436215Z

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.

Observation 3954c034-7da3-47c7-b79e-3e2f12fe913f · outbound

This paper cites an unresolved cited work.

Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion Unresolved cited work

Reference 1311

Resolution: verified exact; doi, observed 2026-08-06T18:26:49.420742Z

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.

Observation 922192f5-c177-49b0-809a-2cb8521d645c · outbound

This paper cites [21] P.J.

Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion [21] P.J

Reference 4041

Resolution: unresolved; no resolver link, observed 2026-08-06T18:26:49.348009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation b2ae1d98-4f08-4cd4-b531-957223216b11 · inbound

AI-Powered Surrogate Modelling for Multiscale Combustion: A Critical Review and Opportunities cites this paper.

AI-Powered Surrogate Modelling for Multiscale Combustion: A Critical Review and Opportunities Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion

Reference 195

Resolution: verified exact; arxiv_id, observed 2026-05-09T02:59:54.257864Z

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.