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Development of Offshore Wind in Atlantic Canada: Regulations, Standards and Technical Challenges

2024· article· en· W4404689083 on OpenAlexaffabout
Mark Fuglem, Paul Stuckey, Ahmed Dereradji-Aouat, Richard McKenna, Freeman Ralph

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsNational Research Council CanadaCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsOffshore wind powerSubmarine pipelineOceanographyWind powerMarine engineeringEnvironmental scienceMeteorologyEngineeringGeologyGeographyElectrical engineering

Abstract

fetched live from OpenAlex

The Canadian Atlantic provinces are looking to work with the federal government to promote the development of offshore wind power to minimize carbon emissions. The province of Newfoundland and Labrador has considerable hydroelectric capacity for domestic use and export and also produces offshore oil for export. The province is looking at developing onshore wind power for the production and export of hydrogen and/or ammonia, and could potentially extend this to the development of offshore wind. As over half of Nova Scotia's electricity is generated from coal, there is a strong impetus to develop renewable sources of electric power, including onshore and offshore wind power. This paper discusses the advantages and challenges of developing offshore wind power across the region and relevant regulations and standards. Emphasis is given to the unique features of the region including the presence of sea ice, significant winter winds and waves, and the potential for hurricanes in the late summer and fall. The paper focuses primarily on Newfoundland and Labrador, and Nova Scotia.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.522

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)0.0000.000

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 head0.010
GPT teacher head0.214
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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 routes2
Has abstractyes

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