Paper Citation Record · LEDGER

Physics-guided spatiotemporal neural models for fuel density prediction

As of 20 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2607.06999.

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

pith.paper-citation-record.v1
2607.06999 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T22:03:33.848601Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

verified exact5
verified fuzzy11
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9b2da47b-da36-426f-b3ee-2e63b5ff2622 · outbound

This paper cites Deep learning models for predicting wildfires from historical remote-sensing data,.

Physics-guided spatiotemporal neural models for fuel density prediction Deep learning models for predicting wildfires from historical remote-sensing data,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.537721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9a1a47bf-850f-42ec-9de1-25efa6e54303 · outbound

This paper cites Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data.

Physics-guided spatiotemporal neural models for fuel density prediction Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T22:06:35.225208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 349b1b54-4c5c-4213-8b87-10cfc8abc770 · outbound

This paper cites Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management.

Physics-guided spatiotemporal neural models for fuel density prediction Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-07-09T22:06:35.223722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7a6aead2-2e44-4d7b-b915-c877679575bc · outbound

This paper cites Gallinas-las dispensas prescribed fire declared wildfire review,.

Physics-guided spatiotemporal neural models for fuel density prediction Gallinas-las dispensas prescribed fire declared wildfire review,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.530814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 91fa67e9-1db5-4a67-ba0d-3fbc489f4683 · outbound

This paper cites URL http://dx.doi.org/10.2737/RMRS-RP-4.

Physics-guided spatiotemporal neural models for fuel density prediction URL http://dx.doi.org/10.2737/RMRS-RP-4

Reference 5

Resolution: verified exact; doi, observed 2026-07-09T22:06:34.937512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bc4fa4d8-d2d1-4553-9251-5b6aef984678 · outbound

This paper cites Quic-fire: A fast-running simulation tool for prescribed fire planning,.

Physics-guided spatiotemporal neural models for fuel density prediction Quic-fire: A fast-running simulation tool for prescribed fire planning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.532692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 341f3892-f2c0-4245-9edb-b19d26afca00 · outbound

This paper cites Emulation of wildland fire spread simulation using deep learning,.

Physics-guided spatiotemporal neural models for fuel density prediction Emulation of wildland fire spread simulation using deep learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.519987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 26567897-b873-408d-a3fa-b1bd06355f03 · outbound

This paper cites Studying wildfire behavior using firetec,.

Physics-guided spatiotemporal neural models for fuel density prediction Studying wildfire behavior using firetec,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.522428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 634ceb34-9c9e-4b29-bfea-01b99cdebccb · outbound

This paper cites Firecast: Leveraging deep learning to predict wildfire spread,.

Physics-guided spatiotemporal neural models for fuel density prediction Firecast: Leveraging deep learning to predict wildfire spread,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.526544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6df07216-4bc5-4707-92a2-dbf8f6f10fe9 · outbound

This paper cites Using convolutional neural networks to predict quic- fire outputs,.

Physics-guided spatiotemporal neural models for fuel density prediction Using convolutional neural networks to predict quic- fire outputs,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.524450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4d6719e2-1c83-4f88-9e44-c2a4338b4329 · outbound

This paper cites Learning u-net without forgetting for near real-time wildfire monitoring by the fusion of sar and optical time series,.

Physics-guided spatiotemporal neural models for fuel density prediction Learning u-net without forgetting for near real-time wildfire monitoring by the fusion of sar and optical time series,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.535157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d4d0cb59-d02f-4beb-9963-957d5ac9650f · outbound

This paper cites Physics-Informed Machine Learning Simulator for Wildfire Propagation.

Physics-guided spatiotemporal neural models for fuel density prediction Physics-Informed Machine Learning Simulator for Wildfire Propagation

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T22:06:35.226525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 089253fe-6bb1-4718-a330-1c825ed9ba01 · outbound

This paper cites Understanding and mitigating gradient flow pathologies in physics-informed neural networks.

Physics-guided spatiotemporal neural models for fuel density prediction Understanding and mitigating gradient flow pathologies in physics-informed neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.528730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8623ee49-9c42-4f96-8d25-13f9af32d0e7 · outbound

This paper cites Physics- informed neural networks: A deep learning framework for solv- ing forward and inverse problems involving nonlinear partial differential equations,.

Physics-guided spatiotemporal neural models for fuel density prediction Physics- informed neural networks: A deep learning framework for solv- ing forward and inverse problems involving nonlinear partial differential equations,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.515876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 597ec11f-f8a4-42f1-835a-16beedbbf169 · outbound

This paper cites Convolutional lstm network: A machine learning approach for precipitation nowcasting,.

Physics-guided spatiotemporal neural models for fuel density prediction Convolutional lstm network: A machine learning approach for precipitation nowcasting,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:06:35.518112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 01ed5feb-10a4-47c8-8dc9-5ca3ece85cb1 · outbound

This paper cites Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers.

Physics-guided spatiotemporal neural models for fuel density prediction Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T22:06:35.222401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dfe56956-42da-43b4-8f77-0068d3d55d1f · outbound

This paper cites ViViT: A Video Vision Transformer.

Physics-guided spatiotemporal neural models for fuel density prediction ViViT: A Video Vision Transformer

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-07-09T22:06:35.216238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4712a720-d07a-480a-b583-567636707638 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Physics-guided spatiotemporal neural models for fuel density prediction Deep Residual Learning for Image Recognition

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-07-09T22:06:35.213146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 809d3c35-1268-4a72-b97c-637620e75a7e · outbound

This paper cites FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.

Physics-guided spatiotemporal neural models for fuel density prediction FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-07-09T22:06:35.219231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.