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Record W4405179303 · doi:10.1109/mele.2024.3473334

A Journey Into Electrical Standardization of Shore Power Connections for Bulk Carriers: Development of a bulk carrier and general cargo ship standard for shore power connections in port.

2024· article· en· W4405179303 on OpenAlexafffund
Hugo Daniel, João Pedro F. Trovão, David Williams, Loïc Boulon

Bibliographic record

VenueIEEE Electrification Magazine · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsUniversité du Québec à Trois-RivièresLa Coop FédéréeUniversité de Sherbrooke
FundersMitacsCanada Research Chairs
KeywordsStandardizationShoreSoftware deploymentEngineeringElectric power systemPort (circuit theory)Electrical engineeringPower (physics)TelecommunicationsMarine engineeringSystems engineeringComputer science

Abstract

fetched live from OpenAlex

This paper presents an insightful analysis of shore power standardization for bulk carriers and general cargo ships, focusing on power demand, berth utilization, and cable management systems. It details the large variety of electrical characteristics and configurations of shore power systems revealing that bulk carriers necessitating a high-voltage connection are responsible for up to 68% of the greenhouse gas emissions. This finding underscores the critical need for developing a high-voltage standard specific to bulk carriers. Additionally, a comprehensive examination of berth usage suggests that strategically equipping the most frequented terminals with a cable management system could enhance global system deployment. Finally, the paper discusses the implications of operational safety and compatibility of shore power standards across the global fleet of bulk carriers and general cargo ships.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.274
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations4
Published2024
Admission routes2
Has abstractyes

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