A hybrid latent class analysis and association rule mining framework to identify injury-related risk patterns in level 2 advanced driver assistance system crashes.
- DOI
- 10.1016/j.aap.2026.108631
- Published
- 2026 Sep
- Container
- Accident; analysis and prevention
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- 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.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1016/j.aap.2026.108631,
title = {A hybrid latent class analysis and association rule mining framework to identify injury-related risk patterns in level 2 advanced driver assistance system crashes.},
author = {Wang J and Harper CD and Hendrickson C},
year = {2026},
journal = {Accident; analysis and prevention},
doi = {10.1016/j.aap.2026.108631},
url = {https://doi.org/10.1016/j.aap.2026.108631}
}RIS
TY - JOUR TI - A hybrid latent class analysis and association rule mining framework to identify injury-related risk patterns in level 2 advanced driver assistance system crashes. AU - Wang J AU - Harper CD AU - Hendrickson C PY - 2026 JO - Accident; analysis and prevention DO - 10.1016/j.aap.2026.108631 UR - https://doi.org/10.1016/j.aap.2026.108631 ER -
APA
J, W., CD, H., & C, H. (2026). A hybrid latent class analysis and association rule mining framework to identify injury-related risk patterns in level 2 advanced driver assistance system crashes.. Accident; analysis and prevention. https://doi.org/10.1016/j.aap.2026.108631
Source records
- pubmed · retrieved 2026-09-25T10:29:53.811Z