Policy Brief - Recognising connectivity and climate change impacts as essential elements for an effective North Atlantic MPA network
Bibliographic record
Abstract
• MPAs can be effective tools for deep-sea ecosystem protection but their effectiveness to counter the<br> impacts of human activities is likely compromised by climate change and ocean acidification.<br> • Maintaining the natural linkage between marine habitats is crucial to healthy marine ecosystems.<br> • Effectiveness should be considered in the context of MPA networks and connectivity.<br> • Area-based planning and management tools in the North Atlantic Ocean’s Area Beyond National<br> Jurisdiction already show a need for climate proofing.<br> • The EU-funded Horizon2020 ATLAS project is linking deep-sea connectivity, bioregions and physical<br> parameters.<br> • Practical implications for the planning of MPA networks include the need to recognise marine exploited<br> areas and deep-sea areas where biodiversity may be more resilient to climate change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".