MétaCan
Menu
Back to cohort
Record W6999449750

Crew safety considerations for the design of fishing vessels

2003· article· en· W6999449750 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2003
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsCrewFishingLift (data mining)Naval architectureMarine safetyPoint (geometry)
DOInot available

Abstract

fetched live from OpenAlex

It is a known fact that vessel motions affect the performance of a fishing vessel in an adverse manner. It could cause fishing to halt, endanger the safety of the vessel and deteriorate the well-being and performance of the crew on board. The effect on the crew can manifest itself in many ways: motion sickness, losing one's balance, reduced capacity to lift objects, etc. This paper particularly focuses on the effects of the vessel motions on the crew. It briefly reviews the current methods developed in the literature to model these effects. It then describes the experience gained in implementing some of these methods into the preliminary ship design at the University of British Columbia (UBC). Some of the results obtained in this study are presented here. This includes a safe cruising speed and the highest operational sea state from the crew safety point of view, and the effects of implementing these methods on the overall outcome of the ship design process.

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)0.000
metaresearch head score (Gemma)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score1.000

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)0.0010.000

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 head0.034
GPT teacher head0.241
Teacher spread0.207 · 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 designSimulation or modeling
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
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueNPARCSame topicMaritime Navigation and SafetyFrench-language works237,207