The IAEA Ocean Acidification International Coordination Centre Capacity Building Program: Empowering Member States to Address and Minimize the Impacts of Ocean Acidification
Bibliographic record
Abstract
Ocean acidification (OA) is threatening marine ecosystems worldwide, with potential follow-on effects on the economies of ocean-dependent communities. The urgent need to mitigate and minimize the impacts of OA is a scientific and political priority, as highlighted by the latest Intergovernmental Panel on Climate Change report (IPCC, 2022) and by the inclusion of OA as a target in the United Nations Sustainable Development Goals (SDG) and the Kunming-Montreal Global Biodiversity Framework. More than 20 years of strong scientific evidence on the impacts of OA provides compelling arguments for urgent CO2 mitigation. Assessing local adaptation possibilities require information at local scales, considering the variabilities in marine ecosystem responses to OA. Sustained measurements and assessment of OA effects on key marine species in developing countries is hindered by a general lack of OA literacy and exacerbated by a lack of infrastructure, instrumentation, and financial support. The International Atomic Energy Agency launched its Ocean Acidification International Coordination Centre (OA-ICC) in 2012, in response to increasing concern about OA by its Member States. The OA-ICC acts as a global hub for coordinated action in three key areas: science, capacity building and communication. The Centre provides opportunities for training and networking for Member States, promotes the development of standardized methodologies and best practices, and provides a number of databases and resources. The OA-ICC works hand in hand with IOC-UNESCO and other international players to ensure a common vision and coordinated international response to address ocean acidification, in the framework of the UN Ocean Decade programme on ocean acidification, OARS (Ocean Acidification Research for Sustainability). Over the past 12 years, the OA-ICC has trained more than 800 scientists from over 100 IAEA Member States on how to study, report and take action on ocean acidification. The Centre has developed a multi-level capacity building program from basic training to collaborative research, tailored to the needs of Member States. Pre- and post-course evaluations have enabled improved format, content, and teaching methods. A technical questionnaire is used to assess the needs and existing capacities of countries. Each institution’s capacity is reflected by a number between 1 (full capacity for OA research) and 4 (lack of basic infrastructure). This presentation will showcase lessons learned and success stories of more than a decade of capacity building on ocean acidification by the Centre and its partners.
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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 | 0.034 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".