Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Spectral identification and classification of dusty stellar sources using spectroscopic and multiwavelength observations through machine learning
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.03403.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:56:28.330697Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-16T12:16:17.039197Z
Reference resolution
0 of 0 outbound references displayed
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- malformed identifier0
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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 5c72327e-4410-494c-82d5-1362e83d527c · inbound
Machine Learning Classification of Young Stellar Objects and Evolved Stars in the Magellanic Clouds Using the Probabilistic Random Forest Classifier cites this paper.
Machine Learning Classification of Young Stellar Objects and Evolved Stars in the Magellanic Clouds Using the Probabilistic Random Forest Classifier Spectral identification and classification of dusty stellar sources using spectroscopic and multiwavelength observations through machine learning
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:56:28.330697Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be9ce566-6f13-4611-8179-bd2d5350900c · inbound
Dusty stellar sources classification by implementing machine learning methods based on spectroscopic observations in the Magellanic Clouds cites this paper.
Dusty stellar sources classification by implementing machine learning methods based on spectroscopic observations in the Magellanic Clouds Spectral identification and classification of dusty stellar sources using spectroscopic and multiwavelength observations through machine learning
Reference 25
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-16T11:56:16.896285Z
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.