Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Correcting for interloper contamination in the power spectrum with neural networks
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2504.06919.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:49:00.805426Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T16:14:15.137392Z
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 c9cde721-59ed-446e-b282-326dbe991177 · inbound
Open Source Planning & Control System with Language Agents for Autonomous Scientific Discovery cites this paper.
Open Source Planning & Control System with Language Agents for Autonomous Scientific Discovery Correcting for interloper contamination in the power spectrum with neural networks
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:49:00.805426Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cafdf140-3efb-4d9a-8163-3b27ef7fefac · inbound
Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study cites this paper.
Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Correcting for interloper contamination in the power spectrum with neural networks
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:41:18.246353Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c95cd35e-7f4f-4199-9bb0-f37a4d969fcc · inbound
Filtering Interlopers with Photometry and Diagnostic Features: A Machine Learning Framework Validated with CSST Slitless Spectroscopy cites this paper.
Filtering Interlopers with Photometry and Diagnostic Features: A Machine Learning Framework Validated with CSST Slitless Spectroscopy Correcting for interloper contamination in the power spectrum with neural networks
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T16:14:15.139093Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.