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Paper Citation Record · LEDGER

Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1708.08843.

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

pith.paper-citation-record.v1
1708.08843 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:10:13.898088Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T05:20:01.763278Z

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 4193c4f6-da24-41f8-879a-8aa911975b35 · inbound

Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning cites this paper.

Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

Reference 117

Resolution
unresolved
no resolver link, observed 2026-08-14T05:10:13.898088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:10:13.898088Z digest=sha256:0bb504ec0735b42ee9ab3e1485a5dec31d3b15a081b8fb89cd5c2d1390783fbd

Observation dfde79c3-fa6c-4bef-895c-ad0785b9fea6 · inbound

Parameter estimation of microlensed gravitational waves with Conditional Variational Autoencoders cites this paper.

Parameter estimation of microlensed gravitational waves with Conditional Variational Autoencoders Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

Reference 100

Resolution
metadata mismatch
local_arxiv, observed 2026-08-12T05:20:01.770345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T05:20:01.494863Z digest=sha256:fc7552f525f3e7135bfc35a0dfa54604923b89a52822a2628573e9e80bf6bfc1

Observation 4686b180-976d-4d85-996e-72c9a4103883 · inbound

Line-of-sight shear in SLACS strong lenses II: validation tests with an extended sample cites this paper.

Line-of-sight shear in SLACS strong lenses II: validation tests with an extended sample Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-03T18:31:03.349994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T18:31:03.349994Z digest=sha256:30219bb359c4faa0b80bea3c1fdd0112336c38f1e00157708750fd221e3f798f