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Record W2753620177 · doi:10.9798/kosham.2017.17.4.307

A Study on the Development of System Dynamics Model for Marine HNS Spill Accidents

2017· article· en· W2753620177 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

VenueKorean Society of Hazard Mitigation · 2017
Typearticle
Languageen
FieldEngineering
TopicMarine and Coastal Research
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsEmergency responseEnvironmental scienceOil spillResponse timeRisk analysis (engineering)System dynamicsComputer scienceBusinessEnvironmental engineering

Abstract

fetched live from OpenAlex

The risk of HNS spill accidents has significantly increased with the traffic of HNS on marine. It highlighted the importance of developing the response system specialized to HNS which has various types and characteristics, however, the limitation is lack of quantitative analysis. In this study, the causal loops for the early response phase of HNS spill accident response was constructed and improvement of the response capability according to the change of major components was confirmed through SD simulation. Also, the result confirmed that the two-step strategy of 15% replacement improved the total response time by 10%. The adoption of two-step strategy is expected to contribute to the compliance with the golden time of the early response. Keywords: HNS Spill Accident, Early Response, System Dynamics, Two-step Strategy

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.305

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 head0.040
GPT teacher head0.291
Teacher spread0.251 · 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