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Paper Citation Record · LEDGER

Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2303.18027.

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

pith.paper-citation-record.v1
2303.18027 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:28:11.077396Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T07:31:24.109678Z

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 397ce05b-4fcb-4f6f-bdd6-b6810636bb2e · inbound

Polish-English medical knowledge transfer: A new benchmark and results cites this paper.

Polish-English medical knowledge transfer: A new benchmark and results Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T05:20:09.130888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:20:09.130888Z digest=sha256:04cabb871dbc50996ba7084376a603932c559b596ae059ce9b6e012d24eeba72

Observation 11dc413d-02cc-4f53-8575-97b11226bca3 · inbound

Technical Report: Small Language Model for Japanese Clinical and Medicine cites this paper.

Technical Report: Small Language Model for Japanese Clinical and Medicine Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-11T10:39:13.226775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:39:13.226775Z digest=sha256:65e92f6a47db08c87de962ae2f3f982c49b33f08e5bd8dcc7445e655832e7d67

Observation 6b748f13-a5e6-4a0c-ba0e-904bb31ace17 · inbound

Stabilizing Reasoning in Medical LLMs with Continued Pretraining and Reasoning Preference Optimization cites this paper.

Stabilizing Reasoning in Medical LLMs with Continued Pretraining and Reasoning Preference Optimization Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-16T10:28:11.077396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:28:11.077396Z digest=sha256:b6da432e35f5c89fe37fb6770f4d5c7ca2d88722ec876bc88ac8da367bf2b95d

Observation 4a59fee1-e889-437c-b70f-5e78391eb159 · inbound

Aligning Large Language Models with Healthcare Stakeholders: A Pathway to Trustworthy AI Integration cites this paper.

Aligning Large Language Models with Healthcare Stakeholders: A Pathway to Trustworthy AI Integration Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-16T04:33:20.715427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:33:20.715427Z digest=sha256:0ca98e1345177b979f03a163066b52066fb17fc907d2fa6352818c54f3f39adf

Observation 2591c9e3-cc51-44f4-85ca-68b12b129d22 · inbound

A Japanese Language Model and Three New Evaluation Benchmarks for Pharmaceutical NLP cites this paper.

A Japanese Language Model and Three New Evaluation Benchmarks for Pharmaceutical NLP Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T15:02:34.282100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:02:34.282100Z digest=sha256:d33e08006257720e81eb087b375557718cffd3171e3e80dbdb09e40c2bec6cc8

Observation 15ea280b-ca5b-4968-bfa2-489e37eabb39 · inbound

KokushiMD-10: Benchmark for Evaluating Large Language Models on Ten Japanese National Healthcare Licensing Examinations cites this paper.

KokushiMD-10: Benchmark for Evaluating Large Language Models on Ten Japanese National Healthcare Licensing Examinations Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T05:39:41.561909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:39:41.561909Z digest=sha256:a5d00914677e367718cc62d70dea2ab1d3d5122423eaa297bf3f6bdd7d8198fb

Observation 473e0470-2905-498d-a8fd-f67854a3936c · inbound

EviCare: Enhancing Diagnosis Prediction with Deep Model-Guided Evidence for In-Context Reasoning cites this paper.

EviCare: Enhancing Diagnosis Prediction with Deep Model-Guided Evidence for In-Context Reasoning Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:21:02.005252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T16:04:15.995849Z digest=sha256:eb8e1709ddb84fdddb7a71ba84d4eba57ddc81cf41098cf51fa4caf992c72940

Observation dd7393b5-e3a4-4e6a-a93b-b1ce620677df · inbound

Medical Incident Causal Factors and Preventive Measures Generation Using Tag-based Example Selection in Few-shot Learning cites this paper.

Medical Incident Causal Factors and Preventive Measures Generation Using Tag-based Example Selection in Few-shot Learning Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:31:24.114518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-12T02:47:27.341864Z digest=sha256:cbcafcab74946432983d9cdfd2896b0d4773fadcb1b9db61d00edc42c6950bd6