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Record W3135333789 · doi:10.1080/25725084.2021.1889869

A study on the preparation of standards for the safety of domestic amphibious ships

2021· article· en· W3135333789 on OpenAlexaboutno aff
Ni-Eun Kim, Young-Soo Park, Sun-Ae Hwang, Min-Jeong Park, Gokhan Camlıyurt

Bibliographic record

VenueJournal of International Maritime Safety Environmental Affairs and Shipping · 2021
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsTourismEngineeringOrder (exchange)Maritime safetyImplementationSafety standardsAeronauticsBusinessTransport engineeringRisk analysis (engineering)GeographyFinance

Abstract

fetched live from OpenAlex

In order to revitalize tourism, there are frequent attempts to introduce amphibious ships in the Republic of Korea. Overseas, amphibious ships are commercialized in the United States, United Kingdom, Australia, Singapore, Canada, etc. Safety cannot be verified in the Republic of Korea due to insufficient systems related to the inspection of amphibious ships. Therefore, in order to secure the safety of amphibious ships, this study presented standards for safe operation through investigations of domestic and foreign amphibious ships operating status and system status, and analysis of accidents related to domestic and foreign amphibious ships. This study proposed the provincial sea area, weather conditions, stability criteria, acquisition system of the number of boarding people, location of water ingress, and inspection period; however, a quantitative review of these criteria is suggested as a future research direction. If the amphibious ship safety implementations are achieved and can be commercialized through this study and further research, it is expected to vitalize the local economy by attracting tourists.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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