Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T15:16:29.646105Z
Paper Citation Record · LEDGER
As of 13 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2508.20214.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T15:16:29.646105Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
15 of 15 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation cc2d1980-268b-43a6-950d-7520df1728ed · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning , " * write output.state after.block = add.period write newline
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8fc3b259-f588-464e-b916-996b3850b473 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning write newline
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 867d2666-2755-45b8-9733-f7aa0ff01ae0 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning 2014, , 52, 43, 10.1146/annurev-astro-081913-035926
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 029cd295-0be6-400f-98f0-3f97661b5fb3 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning Are low luminosity GRBs generated by relativistic jets?
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation adbca021-b077-472c-be5b-c273b9d3a4c6 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning Radio-bright vs. Radio-dark Gamma-ray Bursts -- More Evidence for Distinct Progenitors
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d80de9bb-76ed-482e-806d-d81823e6186e · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning 2024, arXiv e-prints
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 29928c5f-5972-4d35-b731-b2a518ae4b92 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning A., Fishman , G
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1e0b15f-6045-4b7a-a200-55baabdaa413 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning Unresolved cited work
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c35aae7-4060-47a8-922d-ca6f34e54c8d · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning 2022, The Astrophysical Journal, 928, 104, 10.3847/1538-4357/ac54b3
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e356040-fb87-4dd0-80b8-c41f9a46e1a4 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning On the Lack of a Radio Afterglow from Some Gamma-ray Bursts - Insight into Their Progenitors?
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation eff9ad97-1915-4239-9755-7f803672c589 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning M., Gompertz, B., Pe'er, A., Dainotti, M., & Fruchter, A
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45ceb70e-b8af-49e3-906a-1b8b9b40825e · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning I., & Woosley , S
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4b4267a-4631-48b8-a3c3-d8f203c91d0e · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning 2018, Journal of Open Source Software, 3, 10.21105/joss.00861
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0dd847b7-2431-4e44-ac03-ff8d75dd7e19 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning A unified picture for low-luminosity and long gamma-ray bursts based on the extended progenitor of llgrb 060218/SN 2006aj
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e9a24c04-27da-4a88-b8cd-2ca2325d1e52 · outbound
Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning Prompt GRB recognition through waterfalls and deep learning
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
No inbound Pith citation observations are available.