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Record W2988252916 · doi:10.33889/ijmems.2020.5.1.012

A Glance at Transit System Safety

2019· article· en· W2988252916 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

VenueInternational Journal of Mathematical Engineering and Management Sciences · 2019
Typearticle
Languageen
FieldEngineering
TopicSafety Systems Engineering in Autonomy
Canadian institutionsTransport Canada
Fundersnot available
KeywordsRisk analysis (engineering)System safetySafety assuranceFunctional safetyEngineeringManagement systemReliability engineeringSafety engineeringTransport engineeringComputer scienceOperations managementBusiness

Abstract

fetched live from OpenAlex

System safety is a discipline of applying engineering and management principles, criteria, and techniques to achieve acceptable or tolerable risk within the constraints of operational effectiveness, suitability, time, and cost throughout all phases of the system life. System safety engineering is the program to identify hazards, and to eliminate hazards or reduce the associated risks when the hazards cannot be eliminated. System safety management involves plans and activities taken to identify hazards; assess and mitigate associated risks; track, control, close, and document risks encountered in the design, development, test, manufacturing, installation, operation and maintenance, and the disposal of systems, subsystems, and equipment. In this paper, the concept and principle of system safety in the transit system is discussed. The paper also introduces the safety standards, safety life-cycle, Safety Integrity Levels (SILs), safety analysis techniques and safety cases etc.

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: Empirical · Consensus signal: none
Teacher disagreement score0.715
Threshold uncertainty score0.401

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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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