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Record W3042207222 · doi:10.22054/qjpl.2019.34336.1909

حقوق حاکم بر فرآیند برچیدن تاسیسات نفت و گاز

2019· article· fa· W3042207222 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languagefa
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear decommissioningFossil fuelPetroleum engineeringEnvironmental scienceBusinessWaste managementEngineering

Abstract

fetched live from OpenAlex

Decommissioning of petroleum installation and facilities is part of E&P operations that consists of plugging of wells, dismantling of installations and clearance of the site. Technical, financial, economic costs and environmental issues associated with the decommissioning process, compel host countries to enact laws and regulations dealing with all the details of decommissioning operations. However, in some countries, there is no system of law governing the decommissioning project. In the countries with the decommissioning law system, the contents of the laws and regulations are different due to the level of technology and environmental awareness. Identifying law-making gaps in the decommissioning law system of Iran requires the comparative study of the other countries′ laws and regulations especially oil pioneer countries. Therefore, this article at first, analyses the laws and regulations governing the decommissioning of oil and gas installations in the countries with more production capacity such as the UK, the US, Norway and Canada and the countries with lower production capacity such as Nigeria, China, Thailand, Australia, New Zealand, Brunei, Indonesia and the Netherlands comparatively and then deals with decommissioning laws and regulations in Iran.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient 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 score0.240
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.003
Open science0.0050.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0300.001

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 head0.149
GPT teacher head0.504
Teacher spread0.355 · 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
Published2019
Admission routes1
Has abstractyes

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