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Record W7143351550 · doi:10.71465/ajmet1447

Marine Vessel Power Management: Balancing Energy Efficiency and Safety

2024· article· W7143351550 on OpenAlexaff
J. Lonsdale

Bibliographic record

VenueAmerican Journal of Marine Engineering and Technology · 2024
Typearticle
Language
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEfficient energy useReliability (semiconductor)PropulsionRenewable energyEnergy managementEnergy consumptionKey (lock)Fuel efficiencyMarine energyControl (management)

Abstract

fetched live from OpenAlex

Marine vessel power management plays a crucial role in optimizing energy consumption while ensuring operational safety. This article discusses various strategies for balancing energy efficiency with the safety requirements of marine vessels. The integration of energy-saving technologies, renewable energy sources, and advanced control systems can significantly reduce fuel consumption and emissions. However, the complexity of power management systems requires a careful approach to ensure that safety standards are maintained, and operational efficiency is not compromised. This paper explores the key factors influencing power management in modern marine vessels, with an emphasis on smart grid systems, hybrid propulsion technologies, and energy storage solutions. The paper also highlights the role of advanced monitoring and control systems in enhancing the overall safety and reliability of marine vessels.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.001
GPT teacher head0.165
Teacher spread0.164 · 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 designOther design
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
Published2024
Admission routes1
Has abstractyes

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