Bibliographic record
Abstract
Regional initiatives relevant to Arctic environmental protection occurred mainly through the Arctic Council. The council’s ninth ministerial meeting was held in Iqaluit, Canada, and the council’s six working groups continued their co-operative efforts. Documentation from the ministerial meeting and working groups may be found at the council’s website ( ). Other international activities of note included: efforts by the Arctic five coastal states (Arctic 5) towards preventing unregulated high seas fishing in the central Arctic Ocean (CAO) and enhancing protection of polar bears; convening of the fifteenth session of the Barents Euro-Arctic Council; establishment of the Arctic Coast Guard Forum; and final adoption within the International Maritime Organization (IMO) of a Polar Shipping Code. A highlight of the year was the ninth ministerial meeting of the Arctic Council on 24 April in Iqaluit and the issuance of the Iqaluit Declaration 2015. The declaration devotes considerable attention to protecting the unique Arctic environment. Representatives welcomed the launch of the Arctic Adaptation Exchange Portal, which will allow Arctic communities to exchange experiences and best practices in adapting to a changing climate. Arctic states and observers were urged to continue their monitoring and assessment efforts for existing and emerging contaminants. Governments were urged to ratify the Minamata Convention on Mercury in order to promote its entry into force as soon as possible. The meeting welcomed the Framework Plan for Cooperation on Prevention of Oil Pollution from Petroleum and Maritime Activities in the Marine Areas of the Arctic and decided to begin implementing the Framework Plan through various means, including by regular exchanges of experiences among Arctic offshore petroleum regulators. Governments were urged to apply the Arctic Offshore Oil and Gas Guidelines: Systems Safety Management and Safety Culture. A decision was also reached to continue work on a pan-Arctic network of marine protected areas.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.229 | 0.183 |
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".