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Record W3128265785

Chapter 45: Wave, Tidal and Ocean Thermal Energy

2020· article· en· W3128265785 on OpenAlexaff
Theodore Nsoe Adimazoya, Meinhard Doelle

Bibliographic record

VenueSSRN Electronic Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRenewable energyMarine energyTidal powerEnergy currentEnergy developmentClimate changeNatural resource economicsEnvironmental scienceOcean currentEnvironmental resource managementEnvironmental economicsOceanographyEngineeringEconomicsGeologyMarine engineering
DOInot available

Abstract

fetched live from OpenAlex

Ocean renewable energy sources hold the potential to contribute to the options of low-carbon energy sources and enhance the efforts by the global community to slow down climate change. In this Chapter, we provide a brief background on the current state of technology and development of wave, tidal and ocean thermal energy and consider their potential as forms of renewable energy as well as the potential negative environmental footprints of ocean renewable energy installation and development. Secondly, we examine the relevant international legal and policy framework governing ocean energy, highlighting in particular, the absence of a global legal instrument that specifically regulates ocean renewable energy installations at the high seas. Thirdly, we identify current challenges to the roll-out of ocean renewable energy within the international regulatory framework. Lastly, we suggest policy and legal options available to countries to optimize the vast ocean energy resources.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0450.013

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 head0.006
GPT teacher head0.167
Teacher spread0.161 · 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
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
Published2020
Admission routes1
Has abstractyes

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