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Record W2021265015 · doi:10.1109/ever.2013.6521626

All-electric ships—A review of the present state of the art

2013· article· en· W2021265015 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2013 Eighth International Conference and Exhibition on Ecological Vehicles and Renewable Energies (EVER) · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsControl reconfigurationAdaptabilityPropulsionElectrical engineeringState of artElectric power systemState (computer science)Variety (cybernetics)Computer scienceField (mathematics)Power (physics)EngineeringAutomotive engineeringAerospace engineeringSystems engineeringEmbedded systemPhysics

Abstract

fetched live from OpenAlex

Modern navies are exploring ways to power all-electric ships (AES), enabling ships' loads to be powered from the same electrical source as that of the propulsion system, thus avoiding a separate generation system for these loads. AES are envisioned to be equipped with a variety of high power electronic components, pulsed loads like electromagnetic guns and electromagnetic aircraft launchers, machines and cables made of high temperature superconductors that improve efficiency, and highly intelligent controls for adaptability and reconfiguration. This paper presents a review of present state-of-the-art in the field of AES covering all the technological aspects.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.994

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)0.0070.000

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 head0.021
GPT teacher head0.232
Teacher spread0.211 · 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