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Paper Citation Record · LEDGER

Cutting through Complexity: How Data Science Can Help Policymakers Understand the World

As of 10 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 0 inbound Pith citation observations for arXiv:2502.03010.

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

pith.paper-citation-record.v1
2502.03010 v1

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:16:07.939430Z

measured 5 of 5 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 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

5 of 5 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 47b627d8-3348-4ecf-81e0-e8adc6e2ad68 · outbound

This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

Cutting through Complexity: How Data Science Can Help Policymakers Understand the World Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Reference 677

Resolution
unresolved
no resolver link, observed 2026-08-09T10:16:07.931126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:16:07.931126Z digest=sha256:ae6aecceafb1cbdcf26c84acf336d428c3e6cf95708d1d4c42c07c5fbd9d4746

Observation 93f9ab65-889c-4801-b6d5-6ceabe4ecbb0 · outbound

This paper cites Forecasting at Scale.

Cutting through Complexity: How Data Science Can Help Policymakers Understand the World Forecasting at Scale

Reference 1154

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T10:16:08.764488Z

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=pdf_text observed=2026-08-09T10:16:07.935552Z digest=sha256:b4460f824c86082441f80b5f72b8f784096a2bf99275135d398ef43627bb46a9

Observation 2c353ba7-bdf2-47de-ab47-ff217ed8e0cb · outbound

This paper cites Pay Transparency and Gender Equality.

Cutting through Complexity: How Data Science Can Help Policymakers Understand the World Pay Transparency and Gender Equality

Reference 2020

Resolution
metadata mismatch
local_arxiv, observed 2026-08-09T10:16:07.995908Z

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=pdf_text observed=2026-08-09T10:16:07.921095Z digest=sha256:3d0ab338ab177dbe2c0d51c5fdd99d8bad3d305ab6e1918762fafbd7bf8b0895

Observation 58591646-8c2d-4454-bec4-817f69a44967 · outbound

This paper cites Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization.

Cutting through Complexity: How Data Science Can Help Policymakers Understand the World Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-09T10:16:07.926801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:16:07.926801Z digest=sha256:7c6b7550fffc9c0f3f075d4e42de85c03464d0319a3dc89addd419b9e1a9f7ad

Observation 19928c8d-69a3-4f31-b02a-29f0fce0d91a · outbound

This paper cites Bird Distribution Modelling using Remote Sensing and Citizen Science data.

Cutting through Complexity: How Data Science Can Help Policymakers Understand the World Bird Distribution Modelling using Remote Sensing and Citizen Science data

Reference 2023

Resolution
verified exact
local_arxiv, observed 2026-08-09T10:16:07.978234Z

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=pdf_text observed=2026-08-09T10:16:07.939430Z digest=sha256:9c809f5eb5bfeef281a034af360ff2cd96a6602da97dc1f180411e4b0ebb75b9

Pith citing papers

No inbound Pith citation observations are available.