Ecological Insurance of Arctic Oil and Gas Producing Shelf Projects in Russia
Bibliographic record
Abstract
The article deals with problems of ecological insurance of arctic oil and gas producing shelf projects in Russia and possible ways of its development. The authors put forward the method of estimating financial security of operations on eliminating possible ecological damage in case of hydrocarbon spill on arctic shelf oil and gas producing fields and study oil spills on arctic shelf fields ‘Prirazlomnoye’ and ‘Pobeda’. They estimate the cost of measures aimed at elimination of such incidents and propose a special indicator, i.e. financial loss factor for oil spill. Empiric conclusions obtained by comparative analysis of legislation in the field of ecology of entrails use in Russia, Norway, the US and Canada can be used for optimization of the effective Russian legislation and introduction of obligatory ecological insurance. Data of mathematic spill modeling can be applied by insurance companies for calculating insurance premium, by Rosprirodnadzor – for charging penalties and for other supervision bodies – for underwriting oil and gas arctic projects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".