AAVC: An automated framework for high-accuracy ACMG-based variant classification
- DOI
- 10.1016/j.gim.2026.102624
- Published
- 2026-07
- Container
- Genetics in Medicine
- Publisher
- Elsevier BV
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1016/j.gim.2026.102624,
title = {AAVC: An automated framework for high-accuracy ACMG-based variant classification},
author = {R. Arda İnan and Barış Kayaalp and Fatimah Safieh and M. Ece Kars and David Stein and David N. Cooper and Peter D. Stenson and Özlen Konu and Jean-Laurent Casanova and Yuval Itan and A. Nazlı Başak and Tayfun Özçelik},
year = {2026},
journal = {Genetics in Medicine},
doi = {10.1016/j.gim.2026.102624},
url = {https://doi.org/10.1016/j.gim.2026.102624}
}RIS
TY - JOUR TI - AAVC: An automated framework for high-accuracy ACMG-based variant classification AU - R. Arda İnan AU - Barış Kayaalp AU - Fatimah Safieh AU - M. Ece Kars AU - David Stein AU - David N. Cooper AU - Peter D. Stenson AU - Özlen Konu AU - Jean-Laurent Casanova AU - Yuval Itan AU - A. Nazlı Başak AU - Tayfun Özçelik PY - 2026 JO - Genetics in Medicine DO - 10.1016/j.gim.2026.102624 UR - https://doi.org/10.1016/j.gim.2026.102624 ER -
APA
İnan, R. A., Kayaalp, B., Safieh, F., Kars, M. E., Stein, D., Cooper, D. N., Stenson, P. D., Konu, Ö., Casanova, J., Itan, Y., Başak, A. N., & Özçelik, T. (2026). AAVC: An automated framework for high-accuracy ACMG-based variant classification. Genetics in Medicine. https://doi.org/10.1016/j.gim.2026.102624
Source records
- crossref · retrieved 2026-09-27T02:49:28.206Z