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Record W3005070231 · doi:10.1371/journal.pone.0228483

Deep-sea amphipods around cobalt-rich ferromanganese crusts: Taxonomic diversity and selection of candidate species for connectivity analysis

2020· article· en· W3005070231 on OpenAlexfundno aff
Akira Iguchi, Miyuki Nishijima, Yuki Yoshioka, Aika Miyagi, Ryuichi Miwa, Yuichiro Tanaka, Shogo Kato, Takaaki Matsui, Yoshiaki Igarashi, Nobuyuki Okamoto, Atsushi Suzuki

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Biology and Ecology Research
Canadian institutionsnot available
FundersInstitute of GeneticsAgency for Natural Resources and EnergyMinistry of Economy, Trade and Industry
KeywordsSeamountDNA barcodingBiologyCladeDeep seaEvolutionary biologyEcologyZoologyPhylogenetic treePaleontologyGeneticsGeneFishery

Abstract

fetched live from OpenAlex

The aim of this study was to select a candidate deep-sea amphipod species suitable for connectivity analyses in areas around cobalt-rich ferromanganese crusts (CRCs). We applied DNA barcoding based on the mitochondrial protein-coding gene, cytochrome c oxidase subunit I (COI), to specimens collected from the Xufu Guyot (the JA06 Seamount) off southeastern Minami-Torishima Island in the North Pacific, where CRCs are distributed. We used baited traps to collect 37 specimens. Comparison of COI sequences with public reference databases (GenBank, BOLD) showed that almost all of the specimens belonged to the superfamily Lysianassoidea, which is known to be ubiquitous in deep-sea areas. In a molecular taxonomic analysis of these sequences, we detected 11 clades. One of these clades (group 9) composed of 18 sequences and was identified by DNA barcoding as a putative species belonging to Abyssorchomene, which has been reported from the New Hebrides Trench in the South Pacific. We considered this species to be a candidate for connectivity analysis and analyzed its genome by restriction site-associated DNA sequencing. The results showed that the genetic variation in this species is adequate for analyzing connectivity patterns in CRC areas in the future.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.087
GPT teacher head0.229
Teacher spread0.141 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicMarine Biology and Ecology ResearchFrench-language works237,207