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Record W2181220950 · doi:10.1017/s0025315415000983

Demosponges from the Northern Mid-Atlantic Ridge shed more light on the diversity and biogeography of North Atlantic deep-sea sponges

2015· article· en· W2181220950 on OpenAlexfundno aff
Paco Cárdenas, Hans Tore Rapp

Bibliographic record

VenueJournal of the Marine Biological Association of the United Kingdom · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsnot available
FundersNatural Resources CanadaNorwegian Biodiversity Information CentreUppsala UniversitetNorges ForskningsrådUniwersytet WrocławskiUniversitetet i BergenCentre for Environment, Fisheries and Aquaculture Science
KeywordsMid-Atlantic RidgeBiological dispersalOceanographyBiogeographyRidgeDeep seaGeologyEcologyGeographyPaleontologyBiology

Abstract

fetched live from OpenAlex

In July–August 2004, the Mid-Atlantic Ridge Ecosystems (MAR-Eco) expedition collected Demospongiae (Porifera) from the Northern Mid-Atlantic Ridge (MAR) north of the Azores, between 41°N and 61°N. Demosponges were found at 10 stations, at depths ranging from 753 to 3046 m. Twenty-two species were identified: 17 Tetractinellida, one Polymastiida, one Suberitida, two Poecilosclerida and one Dendroceratida. The study of this material is an opportunity to revise the taxonomy and the North Atlantic distribution of each of these deep-sea species. Some species are particularly rare and poorly known (Tetilla longipilis, Tetilla sandalina, Craniella azorica, Polymastia corticata) and two are new to science:Forcepia(Forcepia)toxaferasp. nov. andIotroata paravaridenssp. nov. This study suggests that the MAR is not a longitudinal barrier for the dispersal of deep-sea demosponges while on the contrary, the Charlie-Gibbs Fracture Zone (CGFZ) may be a latitudinal border for the dispersal of deep-sea demosponges, due to great depths and currents.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.023
GPT teacher head0.221
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations49
Published2015
Admission routes1
Has abstractyes

Explore more

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