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Record W2549447996 · doi:10.3303/cet1331006

Applications of Process Safety Concepts to the Hydrogen Economy

2013· article· en· W2549447996 on OpenAlexaff
Paul Amyotte, Fotis Rigas

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSAFERProcess safetyInherent safetyProcess (computing)Risk analysis (engineering)Work (physics)BusinessKey (lock)System safetyProcess safety managementProcess managementDomain (mathematical analysis)Computer scienceWork in processEngineeringOccupational safety and healthPolitical scienceMarketingComputer securityMechanical engineering

Abstract

fetched live from OpenAlex

Hydrogen is widely produced and used in the process industries with growing use in the public domain. While the former area of focus would obviously necessitate process safety considerations, the latter involves activities such as transportation in which occupational safety issues for individuals are paramount. The current research addresses this issue by identifying several areas of application in the hydrogen economy for three key process safety concepts: (i) inherently safer design, (ii) safety management systems, and (iii) the use of case studies. This paper thus illustrates, by means of referenced examples, the transferable nature of key process safety concepts to various features of the emerging hydrogen economy. The primary thesis of this work is the notion that inherently safety design principles, safety management systems, and lessons learned from case histories have broader implications for safety than would be apparent by restricting their use solely to the process industries.

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.

How this classification was reachedexpand

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0090.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0300.001

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 head0.259
GPT teacher head0.594
Teacher spread0.335 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

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