Connectivity Of Bentho-Pelagic Species Among Significant Benthic Areas Off Newfoundland And Labrador
Bibliographic record
Abstract
Poster presentation at ATLAS 3rd General Assembly. Canada is currently working on establishing networks of marine protected areas based on a variety of conservation objectives for a broad range of taxa with contrasting life history characteristics. This study focused on the connectivity of species of cold-water corals among Significant Benthic Areas (SBAs) off Newfoundland and Labrador, Canada. Deep-sea benthic invertebrates could provide a test case for effective MPA networks because of the importance of their larval phase in ensuring colonization, recruitment, and connectivity. We evaluated the scale of potential larval dispersal of several dominant coral species with a significant pelagic larval phase by using an ice-ocean circulation model with a biophysical particle-tracking model. Our simulations show that coral larvae from populations located on the shelf edge may travel several hundreds of kilometres prior to settlement, driven by the strong Labrador Current. A smaller range of potential larval dispersal distances generally characterize corals positioned at other locations (e.g., Labrador Sea). Through these analyses we identify potential linkages (i.e., sources, sink and pathways) of coral larvae among various areas of interest (SBAs), and provide information on the scale of dispersal required to advise policy strategies to protect deep-water corals in this area.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".