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PreprintAll rights reservedmedRxiv

Benchmark Self-Triage (BeST): Comparing Self-Triage Systems and Multiple Generations of OpenAI Models Against Preliminary Expert Consensus

  • L. E. Kroll1
  • A. Seidel
  • J. Schuster
  • E. Steiger
  • T. Schoepke
  • D. von Stillfried
  • BeST Study Group
  1. 1Central Research Institute of Ambulatory Health Care (Zi), Berlin, Germany
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Cite

BibTeXRIS
BibTeX
@misc{kroll2026benchmark,
  title = {{Benchmark Self-Triage (BeST): Comparing Self-Triage Systems and Multiple Generations of OpenAI Models Against Preliminary Expert Consensus}},
  author = {L. E. Kroll and A. Seidel and J. Schuster and E. Steiger and T. Schoepke and D. von Stillfried and BeST Study Group},
  howpublished = {medRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.12.26365287},
  url = {https://www.medrxiv.org/content/10.64898/2026.10.12.26365287v1},
}
RIS
TY  - UNPB
TI  - Benchmark Self-Triage (BeST): Comparing Self-Triage Systems and Multiple Generations of OpenAI Models Against Preliminary Expert Consensus
AU  - L. E. Kroll
AU  - A. Seidel
AU  - J. Schuster
AU  - E. Steiger
AU  - T. Schoepke
AU  - D. von Stillfried
AU  - BeST Study Group
PY  - 2026
DA  - 2026/10/12
PB  - medRxiv
DO  - 10.64898/2026.10.12.26365287
UR  - https://www.medrxiv.org/content/10.64898/2026.10.12.26365287v1
ER  -