MétaCan
Menu
Back to cohort
Record W1534586049

시스템 엔지니어링을 통한 HLA 기반 선박 안전성 평가 시뮬레이션 개발에 관한 연구

2008· article· ko· W1534586049 on OpenAlexaboutno aff
이경호, 한영수, 이병학

Bibliographic record

Venue한국해양공학회지 · 2008
Typearticle
Languageko
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsnot available
Fundersnot available
KeywordsDamagesShipbuildingHigh-level architectureReuseEngineeringProcess (computing)SoftwareComputer scienceRisk analysis (engineering)Operations researchSystems engineeringBusinessInteroperability
DOInot available

Abstract

fetched live from OpenAlex

Many accidents occur on the oceans. Accidents involving ships can cause enormous damage. When an accident occurs, the cost of environmental restoration can bankrupt even a top-ranked international company. The potential damages resulting from ship accidents hare resulted in many international agreements such as MARPOL, SOLAS, ISM Code, etc. The viability of damaged ships has become more and more important. A damaged ship's viability and cargo safety can be improved by a safety assessment design procedure. We consider the shipbuilding industry's distributed characteristics to define a safety assessment system with software engineering-based requirements analysis. We used a distributed network-based simulation method (HLA - High level architecture), because of ease of reuse and expansion of existing components to other situations, arid because it is a military standard. HLA is the standard for distributed network-based simulation in many countries including the United States, Canada, Israel, and Korea. The paper describes research to develop a prototype of a network-based safely assessment simulation system by software engineering basal analysis.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.443
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.079
GPT teacher head0.299
Teacher spread0.220 · 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
GenreMethods

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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same venue한국해양공학회지Same topicAdvanced Software Engineering MethodologiesFrench-language works237,207