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Record W4234682025 · doi:10.1002/9781118476406.emoe351

Introduction

2017· other· en· W4234682025 on OpenAlexaff
Faisal Khan, Seyed Javad Hashemi

Bibliographic record

VenueEncyclopedia of Maritime and Offshore Engineering · 2017
Typeother
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRisk analysis (engineering)Context (archaeology)Risk managementRisk assessmentProcess (computing)Submarine pipelineComputer scienceBusinessEnvironmental resource managementEnvironmental planningEngineeringEnvironmental scienceGeographyComputer security

Abstract

fetched live from OpenAlex

Abstract Development of natural resources in offshore and marine environments presents significant technical and logistical challenges. There is a collective need for the offshore and marine operators to demonstrate that risks are being adequately controlled. The purpose of risk assessment is to help all stakeholders understand the risks to people, assets, and the environment and address potential major hazards in a structured manner. This article provides a general outline for risk assessment and reviews different approaches for risk assessment of offshore and marine operations. It also identifies the key marine hazards and review methods for the assessment of probabilities and consequences of marine hazards. A general framework for development, implementation, and maintenance of risk management process is provided and methods for risk mitigation and reduction are discussed. The purpose of the article is to give the operators a general overview of the process of conducting risk assessments and management in the context of offshore and marine operations to ensure all applicable hazards are identified and the risks are reduced to a level that is as low as reasonably practicable (ALARP).

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.134
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.271
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2017
Admission routes1
Has abstractyes

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