Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Artificial intelligence applied to the automatic analysis of absorption spectra. Objective measurement of the fine structure constant
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1606.07393.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T14:43:16.776386Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-22T04:04:35.948143Z
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 a3b59c64-4fdb-4457-b0be-a09dcef2648d · inbound
Cosmo-Learn: code for learning cosmology using different methods and mock data cites this paper.
Cosmo-Learn: code for learning cosmology using different methods and mock data Artificial intelligence applied to the automatic analysis of absorption spectra. Objective measurement of the fine structure constant
Reference 119
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:43:16.776386Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ab7df1b-bfb8-4bd4-a8a7-c856a9549fcc · inbound
Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest cites this paper.
Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest Artificial intelligence applied to the automatic analysis of absorption spectra. Objective measurement of the fine structure constant
Reference 203
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T04:04:35.950770Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 8db08ece-c85b-4d86-b207-a7e4155289b4 · inbound
Uncertainty-Aware Deep Learning for the Ly$\alpha$ Forest: CNN-Based Absorber Detection and Characterization cites this paper.
Uncertainty-Aware Deep Learning for the Ly$\alpha$ Forest: CNN-Based Absorber Detection and Characterization Artificial intelligence applied to the automatic analysis of absorption spectra. Objective measurement of the fine structure constant
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T06:51:29.075290Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.