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Record W3043647929 · doi:10.1002/prs.12177

A framework for the risk assessment of residual hazardous material in the dynamic environment of a composite production process considering operational time variation

2020· article· en· W3043647929 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

VenueProcess Safety Progress · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsHazardous wasteRisk analysis (engineering)Process (computing)Production (economics)Risk assessmentResidual riskContext (archaeology)ResidualReliability engineeringOperational riskDynamic assessmentProcess safetyProduct (mathematics)EngineeringWork in processComputer scienceRisk managementOperations managementBusinessWaste managementComputer security

Abstract

fetched live from OpenAlex

Abstract In the chemical product production process, activities relating to the transportation and storage of residual hazardous materials increase the risk of workplace contamination and associated negative impacts on worker health and safety. In this context, the dynamic nature of the process complicates the study of the parameters underlying the related operational risks. The current operational risks assessment standard, ISO 31000, cannot provide a practical pathway to assess risks in dynamic operational environments. We, therefore, model a dynamic environment to investigate the effect of functional time variation on risk assessment. Verification of the claimed effect will show that even with rigorous instruction when using the available equipment, the process cannot fully conform to current safety standards.

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)0.004
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.039
GPT teacher head0.366
Teacher spread0.327 · 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