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Record W4226086734 · doi:10.1615/interjalgae.v24.i1.20

Distribution of Algae of the Genus Savoiea M.J.Wynne (Ceramilaes, Rhodophyta) in the Northern Pacific

2022· article· en· W4226086734 on OpenAlexaboutno aff
О. Н. Селиванова, Г. Г. Жигадлова

Bibliographic record

VenueInternational Journal on Algae · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
Fundersnot available
KeywordsCeramialesRhodomelaceaeAlgaeGenusBiogeographyGeographyBiologyPacific oceanRange (aeronautics)EcologyOceanographyGeology

Abstract

fetched live from OpenAlex

Having assessed the diversity and biogeography of a number of marine algae of the order Ceramiales, in collaboration with Canadian phycologists, it was thought that the species, which was considered to be widespread throughout the North Pacific, actually had a more limited geographical distribution. However, further molecular studies revealed genetic similarity between some algae from Russian waters and the Pacific coast of North America. The members of the family Rhodomelaceae (Ceramiales), formerly belonging to the genus Pterosiphonia, and now representing the genus Savoiea, are among them. As a result of our study, we have clarified the taxonomic status of the Savoiea species, and their range in the Russian area of the Pacific Ocean. Wide distribution of S. bipinnata (Postels & Ruprecht) M.J.Wynne and S. hamata (Sinova) Wynne in the northwestern Pacific was confirmed, but it was noted that S. arctica (J.Agardh) M.J.Wynne is reliably found only in the northern seas of Russia, and indication of this species in the Pacific Russian area is likely erroneous. On the contrary, the growth of S. robusta (N.L.Gardner) Wynne in the northwestern Pacific, first discovered in Kamchatka, is validated by distinct morphological and anatomical features of the studied samples, as well as our genetic studies.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.025
GPT teacher head0.231
Teacher spread0.206 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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