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Record W3200723846 · doi:10.3897/zookeys.1060.63307

Rossellid glass sponges (Porifera, Hexactinellida) from New Zealand waters, with description of one new genus and six new species

2021· article· en· W3200723846 on OpenAlexafffund
Henry M. Reiswig, Martin Dohrmann, Michelle Kelly, Sadie Mills, Peter J. Schupp, Gert Wörheide

Bibliographic record

VenueZooKeys · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsUniversity of Victoria
FundersSerono Symposia International FoundationLudwig-Maximilians-Universität MünchenMinistry of Business, Innovation and EmploymentBundesministerium für Bildung und ForschungUniversity of VictoriaGEOMAR Helmholtz-Zentrum für Ozeanforschung KielNational Institute of Water and Atmospheric Research
KeywordsExtant taxonTaxonomy (biology)SpongeBiologyGenusZoologyFaunaCruiseEcologyOceanographyPaleontologyEvolutionary biologyGeology

Abstract

fetched live from OpenAlex

New Zealand's surrounding deep waters have become known as a diversity hotspot for glass sponges (Porifera: Hexactinellida) in recent years, and description and collection efforts are continuing. Here we report on eight rossellids (Hexasterophora: Lyssacinosida: Rossellidae) collected during the 2017 RV Sonne cruise SO254 by ROV Kiel 6000 as part of Project PoribacNewZ of the University of Oldenburg, Germany. The material includes six species new to science, two of which are assigned to a so far undescribed genus; we further re-describe two previously known species. The known extant rossellid diversity from the New Zealand region is thus almost doubled, from nine species in five genera to 17 species in eight genera. The specimens described here are only a small fraction of hexactinellids collected on cruise SO254. Unfortunately, the first author passed away while working on this collection, only being able to complete the nine descriptions reported here. The paper concludes with an obituary to him, the world-leading expert on glass sponge taxonomy who will be greatly missed.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.636

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.207
Teacher spread0.190 · 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 designBench or experimental
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

Citations7
Published2021
Admission routes2
Has abstractyes

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