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Record W2326651084 · doi:10.1115/omae2004-51265

Ocean Energy in British Columbia, Canada: Risk and Rewards

2004· article· en· W2326651084 on OpenAlex
Niels Nielsen, Neil Blaikie

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsBC Hydro (Canada)
Fundersnot available
KeywordsMarine energyWave powerRenewable energyResource (disambiguation)Energy technologyEnergy (signal processing)Energy developmentSubmarine pipelineNew energyElectric powerBusinessEnvironmental economicsEnvironmental resource managementEnvironmental scienceEngineeringOceanographyPower (physics)Computer scienceElectrical engineeringGeologyEconomics

Abstract

fetched live from OpenAlex

The development of Ocean Wave Energy is a leading edge use of primarily existing concepts and technology in a potentially hostile environment. Spawned in part by other offshore industrial and energy related developments, the challenge for ocean wave technology companies has been to harness the huge amounts of this available energy in a safe and efficient manner. With the West Coast of BC having excellent resource potential, electric utilities, power developers and governments have a particular interest in whether Ocean Wave Energy technology has advanced sufficiently to enable development at the near commercial level as a potential future source of renewable energy. This paper will discuss the ocean wave energy potential for BC, how it might be developed, the rewards of successful implementation and the risks that need to be managed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.313

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 head0.002
GPT teacher head0.135
Teacher spread0.132 · 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

Quick stats

Citations0
Published2004
Admission routes2
Has abstractyes

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