MétaCan
Menu
Back to cohort
Record W6963880189 · doi:10.22054/qjpl.2021.56346.2511

Geoengineering and the Approach of International Environmental Documents Towards It's Regulation

2022· article· en· W6963880189 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Geoengineering
Canadian institutionsnot available
Fundersnot available
KeywordsGeoengineeringOpposition (politics)ConventionClimate changeGlobal warmingMontreal ProtocolOzone layer

Abstract

fetched live from OpenAlex

Climate change is considered to be the biggest crisis of the present era, and traditional approaches have not been very effective to deal with it yet. Thus, in recent decades, geoengineering which includes two main methods of carbon dioxide removal and solar radiation management has come to the attention of countries. Like other emerging technologies, besides its benefits, most important of which to combat climate change, due to scientific uncertainty, they might have harmful effects on the environment. The present article has aimed to describe geoengineering methods and their environmental pros and cons. The findings of the article show that although the geoengineering methods in international environmental treaties are scattered, mostly in the form of implicit expressions, the rules and the actions of member states indicate the different and sometimes contradictory attitudes toward geoengineering, which varies from explicit or implicit approval of some methods, especially in treaties related to climate change, to explicit and implicit opposition of others, such as the Convention on Biological Diversity, the London Protocol, and the Ozone Conservation Convention. This dispersion is so great that a specific legal system cannot be assumed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0230.000

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 head0.120
GPT teacher head0.446
Teacher spread0.326 · 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.

Study designObservational
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicClimate Change and GeoengineeringFrench-language works237,207