Bibliographic record
Abstract
Presentation held at the Arctic Workshop of the Transatlantic Ocean Research Alliance 23-24 February 2017 Venue: Rue du Champ de Mars, 21 – B-1050 Brussels (BE) Synopsys Rapid Arctic changes are impacting its own fragile ecosystem and society, and are also, on a broader scale, influencing global changes to the climate system and to sea level. Arctic research and observation are essential to monitor and predict the evolution of these changes. The Arctic, through its interplay with the Atlantic, is part of the EU-US-Canada Transatlantic Ocean Research Alliance launched by the trilateral Galway declaration in May 2013. The Alliance triggered the decision to invest in a broad package of Arctic research activities in Work Programme 2016-17 of Horizon 2020. Three large research projects have already been selected and will begin in late 2016. In this occasion, the European Commission has decided to organise an Arctic Workshop under the Transatlantic Ocean Research Alliance flagship to build on this positive momentum and to further the scientific partnerships on the Arctic between the EU, the US and Canada. Moreover, the Arctic Workshop will also contribute to establishment of the strategies and international efforts to work on the deliverables identified at the recent White House Arctic Science Ministerial meeting on 28th September 2016. In particular, the discussion will focus on the building of an integrated Arctic observing system and to advance towards sustained Arctic observations. The Arctic Workshop will take place in Brussels on 23-24 February 2016. The mornings will be dedicated to show-case of the projects and initiatives in place in Europe, United States and Canada. The afternoon of the first day we will ask the participants to split in two groups to discuss on • "Status of data availability and strategies to build an integrated data access platform "and; • "Key Arctic Change variables for an operational/science integrated Arctic observing system". The objective of the afternoon discussion will be to take stock of the outcomes of the projects and initiatives which are more advanced in their implementation and to confront the different approaches to build synergies, avoid double efforts and identify eventual gaps. The feedback form these discussion sessions will contribute to the identification of future concrete actions for collaboration addressing the priorities set out in the context of the Transatlantic Ocean Research Alliance and, more broadly, the White House Arctic Science Ministerial. The afternoon of the second day will focus on the identification of strategies and mechanisms to facilitate international Arctic science cooperation. The objective will be to contribute to the drafting of a white paper to be presented, and discussed, in a dedicated session at the next ASSW in Prague.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.609 | 0.420 |
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".