Seamount physiography and biology in North-East Atlantic and Mediterranean Sea
Bibliographic record
Abstract
Abstract. This work aims at characterising the seamount physiography and biology in the OSPAR Convention limits (North-East Atlantic Ocean) and Mediterranean Sea. We first inferred potential abundance, location and morphological characteristics of seamounts, and secondly, summarized the existing biological, geological and oceanographic in-situ research, identifying examples of well-studied seamounts. Our study showed that the seamount population in the OSPAR area (North-East Atlantic) and in Mediterranean Sea is large with around 1061 and 202 seamount-like features, respectively. Similarly, seamounts occupy large areas of about 1 116 000 km2 in the OSPAR region and of about 184 000 km2 in the Mediterranean Sea, which is much larger than previously thought. The presence of seamounts in the North-East Atlantic has been known since the late 19th Century but overall knowledge regarding seamount ecology and geology is still relatively poor. Only 37 seamounts in the OSPAR area (3.5% of all seamounts in the region), 22 in the Mediterranean Sea (9.2% of all seamounts in the region) and 25 in the North-East Atlantic south of the OSPAR have in-situ information. Seamounts mapped in both areas are in general very heterogeneous, showing diverse geophysical characteristics. These differences will likely affect the biological diversity and production of resident and associated organisms.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".