Paper Citation Record · LEDGER

Per-Object Systematics using Deep-Learned Calibration

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2003.11099.

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

pith.paper-citation-record.v1
2003.11099 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:28:03.884732Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T19:21:46.852428Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 4f45445f-6849-4a32-850f-7adbdf27acc5 · inbound

Amplitude Uncertainties Everywhere All at Once cites this paper.

Amplitude Uncertainties Everywhere All at Once Per-Object Systematics using Deep-Learned Calibration

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:21:46.855340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6d86a502-ed67-43a3-bc2c-ce306cfa2770 · inbound

Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties cites this paper.

Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties Per-Object Systematics using Deep-Learned Calibration

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-05T13:28:03.884732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33914901-562a-454e-ba5d-0c22ae41b2c8 · inbound

Forecasting Generative Amplification cites this paper.

Forecasting Generative Amplification Per-Object Systematics using Deep-Learned Calibration

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T21:31:21.962082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63f29834-5dd0-46a9-ade4-ec97ddeb5d41 · inbound

Agentic Re-Casting using Agentic Re-Simulations cites this paper.

Agentic Re-Casting using Agentic Re-Simulations Per-Object Systematics using Deep-Learned Calibration

Reference 186

Resolution: unresolved; no resolver link, observed 2026-08-01T04:29:17.332215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 476ef2ed-6419-4220-824c-245bbd558359 · inbound

Neural Control Variates at LO and NLO cites this paper.

Neural Control Variates at LO and NLO Per-Object Systematics using Deep-Learned Calibration

Reference 88

Resolution: unresolved; no resolver link, observed 2026-07-30T18:12:21.901220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.