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Paper Citation Record · LEDGER

SearchRAG: Can Search Engines Be Helpful for LLM-based Medical Question Answering?

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2502.13233.

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

pith.paper-citation-record.v1
2502.13233 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 2026-08-17T06:30:58.91139+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:22:46.444442Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T05:57:41.606368Z

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 2d94a4be-7d04-4ddc-aded-a0987fe79986 · inbound

Supervising the search process produces reliable and generalizable information-seeking agents cites this paper.

Supervising the search process produces reliable and generalizable information-seeking agents SearchRAG: Can Search Engines Be Helpful for LLM-based Medical Question Answering?

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:22:25.381371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-23T02:18:27.204122Z digest=sha256:1b5abb0d2c7924ba2810ff56001f60e1f5da3e15f6a957d551846f2a22fe43e0

Observation a113dfbf-884a-4d75-994b-5adc273e4939 · inbound

CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis cites this paper.

CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis SearchRAG: Can Search Engines Be Helpful for LLM-based Medical Question Answering?

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T23:22:46.444442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:22:46.444442Z digest=sha256:012ed883522953b20db72bb249ef37d998a4434e1f13910965cc4079a5ad7b51

Observation 54046555-b703-48b9-9468-a8285f54f3b2 · inbound

The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes cites this paper.

The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes SearchRAG: Can Search Engines Be Helpful for LLM-based Medical Question Answering?

Reference 211

Resolution
verified exact
arxiv_id, observed 2026-07-03T05:57:41.607895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-27T12:59:51.091008Z digest=sha256:66b5bcdc97be75ca5d46d01bee20dd4d2f6c2197ef0803e408798a73859d37fc