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Paper Citation Record · LEDGER

HOLISMOKES -- IV. Efficient mass modeling of strong lenses through deep learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2010.00602.

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

pith.paper-citation-record.v1
2010.00602 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T11:50:26.030339Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T20:06:29.566536Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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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 07abfeda-364b-44e5-9b29-6d371732b2fb · inbound

Prospect for Detection of Strongly Lensed Multi-messenger Signals of Binary Neutron Star Mergers cites this paper.

Prospect for Detection of Strongly Lensed Multi-messenger Signals of Binary Neutron Star Mergers HOLISMOKES -- IV. Efficient mass modeling of strong lenses through deep learning

Reference 65

Resolution
verified exact
local_arxiv, observed 2026-07-09T20:06:29.567938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-11T11:50:26.030339Z digest=sha256:74765c8dadacd66f5b4afab74122bd8d2f7d6f18b7f9a51e8c62667815b28ca7