Overview of Measures Specifically Designed to Prevent Oil Pollution in the Arctic Marine Environment from Offshore Petroleum Activities
Bibliographic record
Abstract
Abstract The Kiruna Ministerial Meeting of the Arctic Council in 2013 identified an action to develop an overview of the existing and potential technical and operational safety measures specifically designed to prevent oil pollution in the Arctic marine environment due to offshore petroleum activities. The Task Force on Arctic Marine Oil Pollution Prevention (TFOPP) was subsequently established and delivered its recommendations to the Iqaluit Ministerial Meeting in 2015. The report presented in this paper is a response to one of the recommendations. The report (Haver, 2015) was prepared by Proactima for the Norwegian Petroleum Safety Authority acting on behalf of the Norwegian Ministry of Foreign Affairs. The final report was delivered to the Ministry of Foreign Affairs for further processing within the Arctic Council. A comprehensive overview of measures has been established based on contributions from the industry and R&D institutions through a baseline survey in addition to reviewing open sources. The report endeavours to provide a broad overview, covering the most important areas subject to the scope of work. An objective of the report is to provide a catalogue of existing pollution prevention measures for petroleum activities in the Arctic and a basis for evaluating the need for development of new measures. The aim is to make best use of existing knowledge in operations and optimum use of resources when considering future research and development projects. The report demonstrates that extensive research and development initiatives have been ongoing for several decades related to enhancing the safety of offshore petroleum activities in the Arctic and cold climate regions. The report, although being a documentation of facts, presents observations, recommendations and suggestions for further work. The objective of this paper is to make the report known to the wider community of petroleum professionals with special interest in activity in the Arctic. The paper should provide sufficient information to motivate the community to review the report and make use of it where applicable. Note: This paper is an extract of the report (Haver, 2015) and the text is primarily taken directly from the report. The report has extensive references that are not included in this paper. The report is openly available for download at: http://www.ptil.no/getfile.php/PDF/Rapporter/Overview%20of%20measures_report_TFOPP.pdf
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".