Making ocean climate effects studies matter to society
Bibliographic record
Abstract
Abstract The 5th International Conference on the Effects of Climate Change on the World’s Ocean (ECCWO5) was held from April 17 to 21, 2023, in Bergen, Norway. Some seven hundred ocean experts from around the world gathered online and under the sunny blue sky at Bryggen, a historic waterfront harbor. The ECCWO conference series was initiated in 2008, aiming to better understand the impacts of climate change on ocean ecosystems, the services they provide, and the people, businesses, and communities that depend on them. PICES, ICES, IOC, and FAO were major sponsors and organizers of this event with the Institute of Marine Research, Norway, as the local host. The outcomes of the symposium highlighted the importance of tipping points and the fact that the effects of climate change on habitat-building species are dramatic and are impacted by marine heat waves. A robust and adaptive ecosystem approach to fisheries management under climate change is recommended, and low-emission fishing should be implemented broadly. The effects of climate change on ocean deoxygenation need more research. Climate impact assessments should be routinely performed for key ecosystem components. There needs to be more focus on social-ecological approaches and effective stakeholder engagement. We encourage work across the boundaries of disciplines and geography to ensure rapid development and uptake of good practices in science-based advice and management so that they can be adopted by the fishing and aquaculture industry. The ECCWO conference series has contributed to building and maintaining a research community centered on climate change effects on the ocean that will be important moving forward.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".