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Record W2989882083

Doprinos smanjenju rizika sudara između brodova simuliranjem radnji izbjegavanja sudara

2019· dissertation· hr· W2989882083 on OpenAlexaboutno aff
Marko Šuljić

Bibliographic record

Venuenot available
Typedissertation
Languagehr
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)Quarter (Canadian coin)CollisionPoint (geometry)Operations researchComputer scienceEngineeringSimulationComputer securityMathematicsGeographyPhysics
DOInot available

Abstract

fetched live from OpenAlex

In this graduate thesis, the term of Close Quarter Situation, is analyzed. This term is mentioned in the International Regulations for Preventing Collisions at Sea and although mentioned the definition of the term is not clear. In this thesis there are several definitions of Close Quarter Situation given by different authors, these authors and experts based their definitions on their experience in the court law. The difference between the definitions of the mentioned term has been an inspiration for the research carried on the navigational simulator. For the research on the simulator the ships were divided into two main groups: fine form ships and full form ships. Using mentioned groups of different scenarios were defined and than simulated on the navigational simulator. A total of 60 simulations were carried out, with the goal to getting the values of the dCPA (distance to closest point of approach) and TCPA (time to closest point of approach), the values at which ship still can avoid collision with it's own action.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0250.020

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 head0.243
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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Same topicMaritime Navigation and SafetyFrench-language works237,207