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Record W2077883425 · doi:10.1002/prs.10253

Development of a process safety culture of chemical engineers

2008· article· en· W2077883425 on OpenAlexaff
Maxime Mckay, J.P. Lacoursière

Bibliographic record

VenueProcess Safety Progress · 2008
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsProcess safetySafety cultureProcess (computing)Vulnerability (computing)Process safety managementEngineeringHazardRisk analysis (engineering)Key (lock)Work in processEngineering managementOperations managementBusinessComputer securityComputer scienceManagementHazardous wasteWaste management

Abstract

fetched live from OpenAlex

Abstract Chemical engineers are frequently responsible for designing and operating process facilities. These facilities could cause major accidents with consequences on site and off site. Equilibrium has to be maintained between production pressure and safety requirements. This equilibrium can only be achieved if the people involved with the process plant develop and maintain a strong process safety culture. Lessons from the Challenger, Columbia, BP Texas City accidents, etc. indicate that there are five important key organization culture themes that need to be taken into account: Maintain sense of vulnerability Establish an imperative for safety Perform valid/timely hazard/risk assessments Ensure open and frank communications Learn and advance the culture This paper will describe how a chemical engineer can integrate these as a safety roadmap. © 2008 American Institute of Chemical Engineers Process Saf Prog, 2008

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0090.003
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.349
Teacher spread0.304 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations7
Published2008
Admission routes1
Has abstractyes

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