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Paper Citation Record · LEDGER

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning

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.

pith.paper-citation-record.v1
2508.20214 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:16:29.646105Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cc2d1980-268b-43a6-950d-7520df1728ed · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning , " * write output.state after.block = add.period write newline

Reference 1

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unresolved
no resolver link, observed 2026-08-05T15:16:29.585392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.585392Z digest=sha256:f62e5de2887fe4b289c803f506b7fa9e0eba32533092b5a4c61b87a84af96280

Observation 8fc3b259-f588-464e-b916-996b3850b473 · outbound

This paper cites write newline.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning write newline

Reference 2

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unresolved
no resolver link, observed 2026-08-05T15:16:29.589912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.589912Z digest=sha256:0a33bc3034b536717acdc148ed074e505d4279f66ee1d82ecd6173b4bbd2bf56

Observation 867d2666-2755-45b8-9733-f7aa0ff01ae0 · outbound

This paper cites 2014, , 52, 43, 10.1146/annurev-astro-081913-035926.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning 2014, , 52, 43, 10.1146/annurev-astro-081913-035926

Reference 4

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unresolved
no resolver link, observed 2026-08-05T15:16:29.604289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.604289Z digest=sha256:340bfe677c5a57c1bf9d4ef90ee756a54815350bd44e3e723a45f7e6ad114122

Observation 029cd295-0be6-400f-98f0-3f97661b5fb3 · outbound

This paper cites Are low luminosity GRBs generated by relativistic jets?.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning Are low luminosity GRBs generated by relativistic jets?

Reference 5

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unresolved
no resolver link, observed 2026-08-05T15:16:29.607892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.607892Z digest=sha256:196c76793a014ddb18688d7d7d2f8cda3cd584a487f6576934fa3e2720ce5bfe

Observation adbca021-b077-472c-be5b-c273b9d3a4c6 · outbound

This paper cites Radio-bright vs. Radio-dark Gamma-ray Bursts -- More Evidence for Distinct Progenitors.

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

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unresolved
no resolver link, observed 2026-08-05T15:16:29.611133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.611133Z digest=sha256:f53c89959b0196325a7e372c7636c578e53ee9065fc8049bbe69a0f4149e6679

Observation d80de9bb-76ed-482e-806d-d81823e6186e · outbound

This paper cites 2024, arXiv e-prints.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning 2024, arXiv e-prints

Reference 7

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verified exact
raw_fallback, observed 2026-08-05T15:16:29.857305Z

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.

source=arxiv_source observed=2026-08-05T15:16:29.615377Z digest=sha256:3fdfeb96ddda48323a68980db469d492316381282286393e84f94f8ea0860c56

Observation 29928c5f-5972-4d35-b731-b2a518ae4b92 · outbound

This paper cites A., Fishman , G.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning A., Fishman , G

Reference 8

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unresolved
no resolver link, observed 2026-08-05T15:16:29.618512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.618512Z digest=sha256:8ff758e2d4534848754c350aeb085e702a1a46f00743c05970e1b82983900103

Observation a1e0b15f-6045-4b7a-a200-55baabdaa413 · outbound

This paper cites an unresolved cited work.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning Unresolved cited work

Reference 9

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unresolved
no resolver link, observed 2026-08-05T15:16:29.621792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.621792Z digest=sha256:1177b4316531cb7c99449482fea4382ef239c5b71327dad8a19e146a9bf81c37

Observation 2c35aae7-4060-47a8-922d-ca6f34e54c8d · outbound

This paper cites 2022, The Astrophysical Journal, 928, 104, 10.3847/1538-4357/ac54b3.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning 2022, The Astrophysical Journal, 928, 104, 10.3847/1538-4357/ac54b3

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T15:16:29.624958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.624958Z digest=sha256:fe788b0ba351c57c55e26f0cea2bfde4e6c29162abf930b36383de5373b16b64

Observation 4e356040-fb87-4dd0-80b8-c41f9a46e1a4 · outbound

This paper cites On the Lack of a Radio Afterglow from Some Gamma-ray Bursts - Insight into Their Progenitors?.

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

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:16:29.735850Z

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.

source=arxiv_source observed=2026-08-05T15:16:29.627926Z digest=sha256:b503176738e882d84ac3c22f82b491f3c38823d8919249daf2582ceede552f25

Observation eff9ad97-1915-4239-9755-7f803672c589 · outbound

This paper cites M., Gompertz, B., Pe'er, A., Dainotti, M., & Fruchter, A.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning M., Gompertz, B., Pe'er, A., Dainotti, M., & Fruchter, A

Reference 12

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unresolved
no resolver link, observed 2026-08-05T15:16:29.631160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.631160Z digest=sha256:7c557afea60f5bda5bb12fc06051dff62ca2953015c738780d8cd00226a2be71

Observation 45ceb70e-b8af-49e3-906a-1b8b9b40825e · outbound

This paper cites I., & Woosley , S.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning I., & Woosley , S

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T15:16:29.635850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.635850Z digest=sha256:e99c93574c2441e532b3c79b4ac41a26f5ea8319c565d01c55c12b4e90ecfe6b

Observation c4b4267a-4631-48b8-a3c3-d8f203c91d0e · outbound

This paper cites 2018, Journal of Open Source Software, 3, 10.21105/joss.00861.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning 2018, Journal of Open Source Software, 3, 10.21105/joss.00861

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T15:16:29.639005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.639005Z digest=sha256:d46d472213cc8a0fbd1d39e23eca9c9a4db06009d63a3a044974705f8bf293e4

Observation 0dd847b7-2431-4e44-ac03-ff8d75dd7e19 · outbound

This paper cites A unified picture for low-luminosity and long gamma-ray bursts based on the extended progenitor of llgrb 060218/SN 2006aj.

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

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unresolved
no resolver link, observed 2026-08-05T15:16:29.642944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:16:29.642944Z digest=sha256:3aacdf47f0dcbbe06c71214646762a7acf92c908e61627a33fb8c1410b63aca0

Observation e9a24c04-27da-4a88-b8cd-2ca2325d1e52 · outbound

This paper cites Prompt GRB recognition through waterfalls and deep learning.

Mapping Gamma-Ray Bursts: Distinguishing Progenitor Systems Through Machine Learning Prompt GRB recognition through waterfalls and deep learning

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:16:29.715069Z

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.

source=arxiv_source observed=2026-08-05T15:16:29.646105Z digest=sha256:dc649d2368646379f029ad90363d184b1dc1108cfd248085ffb3ccc9fa752c38

Pith citing papers

No inbound Pith citation observations are available.