Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system.

Borg M, Henriksson J, Socha K, Lennartsson O, Sonnsjö Lönegren E, Bui T, Tomaszewski P, Sathyamoorthy SR, Brink S, Helali Moghadam M

Open source

DOI: 10.1007/s11219-022-09613-1
Published: 2023 Mar 1
Container: Software quality journal
Publisher: Not recorded
Open access: yes

Credibility signals

limited evidence Score 45/100 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. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1007/s11219-022-09613-1,
  title = {Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system.},
  author = {Borg M and Henriksson J and Socha K and Lennartsson O and Sonnsjö Lönegren E and Bui T and Tomaszewski P and Sathyamoorthy SR and Brink S and Helali Moghadam M},
  year = {2023},
  journal = {Software quality journal},
  doi = {10.1007/s11219-022-09613-1},
  url = {https://doi.org/10.1007/s11219-022-09613-1}
}

RIS

TY  - JOUR
TI  - Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system.
AU  - Borg M
AU  - Henriksson J
AU  - Socha K
AU  - Lennartsson O
AU  - Sonnsjö Lönegren E
AU  - Bui T
AU  - Tomaszewski P
AU  - Sathyamoorthy SR
AU  - Brink S
AU  - Helali Moghadam M
PY  - 2023
JO  - Software quality journal
DO  - 10.1007/s11219-022-09613-1
UR  - https://doi.org/10.1007/s11219-022-09613-1
ER  -

APA

M, B., J, H., K, S., O, L., E, S. L., T, B., P, T., SR, S., S, B., & M, H. M. (2023). Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system.. Software quality journal. https://doi.org/10.1007/s11219-022-09613-1

Source records

pubmed · retrieved 2026-09-25T11:31:07.502Z