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Paper Citation Record · LEDGER

Founder-GPT: Self-play to evaluate the Founder-Idea fit

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.12037.

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

pith.paper-citation-record.v1
2312.12037 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:23:10.385614Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a9fc4e8d-075d-4bdc-81aa-d800c1070f20 · inbound

Random Rule Forest (RRF): Interpretable and Manageable Ensembles of LLM-Generated Questions for Predicting Success from Unstructured Data cites this paper.

Random Rule Forest (RRF): Interpretable and Manageable Ensembles of LLM-Generated Questions for Predicting Success from Unstructured Data Founder-GPT: Self-play to evaluate the Founder-Idea fit

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:10.385614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:10.385614Z digest=sha256:e90d05a9f40237f97845081a60710c0556ea4821209993e5fe7b53e55241f3da

Observation e30d6ca2-555c-458b-99b8-c88f4fbf9dd3 · inbound

From Limited Data to Rare-event Prediction: LLM-powered Feature Engineering and Multi-model Learning in Venture Capital cites this paper.

From Limited Data to Rare-event Prediction: LLM-powered Feature Engineering and Multi-model Learning in Venture Capital Founder-GPT: Self-play to evaluate the Founder-Idea fit

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:18:36.366912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:18:35.852796Z digest=sha256:840c164e7032c8a7d5584d329c34f229627391bef300434e5ea505e8a3ef845e