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Paper Citation Record · LEDGER

Supernova Photometric Classification Pipelines Trained on Spectroscopically Classified Supernovae from the Pan-STARRS1 Medium-Deep Survey

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1905.07422.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1905.07422 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:54:41.092423Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:26:54.643978Z

Reference resolution

0 of 0 outbound references displayed

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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 42101466-85fd-4839-8fec-dd47b8557458 · inbound

On the cosmological performance of photometrically classified supernovae with machine learning cites this paper.

On the cosmological performance of photometrically classified supernovae with machine learning Supernova Photometric Classification Pipelines Trained on Spectroscopically Classified Supernovae from the Pan-STARRS1 Medium-Deep Survey

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-14T13:54:41.092423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:54:41.092423Z digest=sha256:f990d75f1445e7c7b08fb73d2921647d001475344c87f71c89c1502b924f1082

Observation 440168cc-4db5-494a-a887-7cea92bb6ccb · inbound

Toward decision-aware AI for LSST-scale time-domain astronomy cites this paper.

Toward decision-aware AI for LSST-scale time-domain astronomy Supernova Photometric Classification Pipelines Trained on Spectroscopically Classified Supernovae from the Pan-STARRS1 Medium-Deep Survey

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:26:54.645408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T03:46:08.276270Z digest=sha256:94d6e5438e8adc15dfa4803fc72b53ac0833599bf5270d8cacfa27bad5f45467