Paper Citation Record · LEDGER

Rainy: Unlocking Satellite Calibration for Deep Learning in Precipitation

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2504.10776.

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

pith.paper-citation-record.v1
2504.10776 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:04:15.481440Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T12:53:06.891867Z

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 ee17f0db-7b1f-45e2-a243-8f9ff0936677 · inbound

SatelliteFormula: Multi-Modal Symbolic Regression from Remote Sensing Imagery for Physics Discovery cites this paper.

SatelliteFormula: Multi-Modal Symbolic Regression from Remote Sensing Imagery for Physics Discovery Rainy: Unlocking Satellite Calibration for Deep Learning in Precipitation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T06:04:15.481440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd2ba2f6-0c71-49fa-903b-d950c71abd9f · inbound

From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion cites this paper.

From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion Rainy: Unlocking Satellite Calibration for Deep Learning in Precipitation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T18:10:15.203628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5e78bed-12f3-46af-b41d-c9b912a19f91 · inbound

Multi-Modal Machine Learning Framework for Predicting Early Recurrence of Brain Tumors Using MRI and Clinical Biomarkers cites this paper.

Multi-Modal Machine Learning Framework for Predicting Early Recurrence of Brain Tumors Using MRI and Clinical Biomarkers Rainy: Unlocking Satellite Calibration for Deep Learning in Precipitation

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-05T12:53:06.896587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a9abf854-2be9-4751-bbf8-bbb71f0cf36e · inbound

A Multimodal Deep Learning Framework for Early Diagnosis of Liver Cancer via Optimized BiLSTM-AM-VMD Architecture cites this paper.

A Multimodal Deep Learning Framework for Early Diagnosis of Liver Cancer via Optimized BiLSTM-AM-VMD Architecture Rainy: Unlocking Satellite Calibration for Deep Learning in Precipitation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T12:53:14.602327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.