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Record W2099206925 · doi:10.5194/bg-10-3039-2013

Seamount physiography and biology in the north-east Atlantic and Mediterranean Sea

2013· article· en· W2099206925 on OpenAlexaff
Telmo Morato, K. Ø. Kvile, Gerald H. Taranto, Fernando Tempera, Bhavani E. Narayanaswamy, Dierk Hebbeln, Gui M. Menezes, Claudia Wienberg, Ricardo S. Santos, T. J. Pitcher

Bibliographic record

VenueBiogeosciences · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Biology and Ecology Research
Canadian institutionsUniversity of British Columbia
FundersFundação para a Ciência e a TecnologiaNatural Environment Research CouncilEuropean CommissionSight Research UK
KeywordsSeamountOceanographyGeologyMediterranean climateMediterranean seaGeographyArchaeology

Abstract

fetched live from OpenAlex

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 the Mediterranean Sea is large with around 557 and 101 seamount-like features, respectively. Similarly, seamounts occupy large areas of about 616 000 km2 in the OSPAR region and of about 89 500 km2 in the Mediterranean Sea. 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 area 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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.032
GPT teacher head0.246
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations47
Published2013
Admission routes1
Has abstractyes

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