حقوق حاکم بر فرآیند برچیدن تاسیسات نفت و گاز
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".