MétaCan
Menu
Back to cohort

Using Boundary Objects for Continuous Compliance in Automotive Development

2024· article· en· W4404952849 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSafety Systems Engineering in Autonomy
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAutomotive industryCompliance (psychology)Computer scienceBoundary (topology)Manufacturing engineeringAutomotive engineeringEngineeringMathematicsPsychologyAerospace engineeringMathematical analysis

Abstract

fetched live from OpenAlex

A major challenge in multidisciplinary environments, such as automotive Original Equipment Manufacturers (OEMs), is managing aggressive development timelines while ensuring the overall safety of products. To continuously keep track of the development, project managers and engineers employ various tools and methodologies. However, sharing and managing the data from different frameworks raises important challenges. In this paper, we introduce an approach that is a result of combining model-based engineering and boundary objects methodology that integrates safety assurance processes with agile development workflows. The purpose of the boundary object is to preserve the constraints, requirements, and procedures of safety processes and to translate the information so that it is useful within an agile development process. We demonstrate the approach’s effectiveness via an example and discuss its potential benefits.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.281
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicSafety Systems Engineering in AutonomyFrench-language works237,207