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Record W2946594119 · doi:10.5296/jpag.v9i2.14559

Comparative International Law: The Scope and Management of Public Participation Rights Related to CCS Activities

2019· article· en· W2946594119 on OpenAlexaboutno aff
Raíssa Moreira Lima Mendes Musarra, Hirdan Katarina de Medeiros Costa

Bibliographic record

VenueJournal of Public Administration and Governance · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
FundersShell BrasilUniversidade de São PauloFundação de Amparo à Pesquisa do Estado de São PauloResearch Centre for Gas Innovation
KeywordsScope (computer science)Corporate governanceAgency (philosophy)European unionAtomic energyPublic participationPresentation (obstetrics)BusinessPublic administrationPolitical scienceBest practiceLawInternational tradeSociologyComputer science

Abstract

fetched live from OpenAlex

The paper proposes the presentation of the public participation item in the regulatory standards of CCS in Australia, Canada, the European Union, the United Kingdom and the United States and their possible relations with the Brazilian configuration. The choice of territories is due to the existence of the item in its legal norms and or regulations. The standards available from the International Energy Agency (IEA) database on Carbon Capture, Transport and Storage were used. The methodology used is the comparative, cumulatively with the deductive method, assuming that public participation is a fundamental issue for the governance of CCS activities and that Brazil, when inserting such activities into its code, should take into account the adoption of the best practices of public participation, which, in addition to being consultative, provides deliberative powers to citizens.

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)0.022
metaresearch head score (Gemma)0.045
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 score0.022
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0070.008
Science and technology studies0.0050.019
Scholarly communication0.0110.015
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.033
GPT teacher head0.289
Teacher spread0.255 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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