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Record W4395031420 · doi:10.29173/alr2765

Prevailing Winds: Regulatory Frameworks and Commercial Realities for Developing Wind and Green Hydrogen Projects in Nova Scotia and Newfoundland and Labrador

2023· article· en· W4395031420 on OpenAlexaffvenueabout
K. Grant, James D. Gamblin, Gregory A.C. Moores, G. John Samms

Bibliographic record

VenueAlberta Law Review · 2023
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsGovernment of Newfoundland and LabradorNova Scotia Health Authority
Fundersnot available
KeywordsNova scotiaNova (rocket)GeographyRegional scienceArchaeologyEngineeringAeronautics

Abstract

fetched live from OpenAlex

Government and industry in Nova Scotia and Newfoundland and Labrador are displaying increasing enthusiasm for onshore and offshore wind projects as well as associated development of green hydrogen resources. There are possible gaps between the commercial realities of wind-related development and both existing and proposed regulatory regimes in comparison with select international offshore regimes. The regulatory context and the makeup of the electrical grid in Nova Scotia and Newfoundland and Labrador have both parallels and distinctions, providing for differing trajectories when it comes to the development of onshore wind, offshore wind, and green hydrogen. More mature wind and hydrogen regulatory regimes within the European Union provide indicators of challenges that may be faced by both provinces as each try to rapidly pursue wind and green hydrogen development.

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)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.446

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.004
Scholarly communication0.0090.001
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.279
Teacher spread0.248 · 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
Published2023
Admission routes3
Has abstractyes

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