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Record W2953977481 · doi:10.1111/1462-2920.14729

Hydrothermal vent protistan distribution along the Mariana arc suggests vent endemics may be rare and novel

2019· article· en· W2953977481 on OpenAlexafffund
Sheryl Murdock, S. Kim Juniper

Bibliographic record

VenueEnvironmental Microbiology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsOcean Networks Canada SocietyUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsBiologyEndemismProtistAbundance (ecology)EcologyCladeHydrothermal ventHabitatEcosystemPhylogeneticsPaleontology

Abstract

fetched live from OpenAlex

Elucidation of the potential roles of single-celled eukaryotes (protists) in ecosystem function and trophodynamics in hydrothermal vent ecosystems is reliant on information regarding their abundance, distribution and preference for vent habitats. Using high-throughput 18S rRNA gene sequencing on a diverse suite of hydrothermally influenced and background water samples, we assess the diversity and distribution of protists and identify potential vent endemics. We found that 95% of the recovered sequences belong to operational taxonomic units (OTUs) with a cosmopolitan distribution across vent and non-vent habitats. Analysis of 'vent only' OTUs found in more than one vent sample and co-occurrence network analysis comparing protist groups to extremophilic reference organisms suggest that the most likely vent endemics are infrequently encountered, potentially in low abundance, and belong to novel lineages, both at the phylum level and within defined clades of Rhizaria and Stramenopila. Potential endemism is inferred for relatives of known apusomonads, excavates and some clades of Syndiniales. Similarity in community composition among samples was low, indicating a strong stochastic component to protist community assembly and suggesting that rare endemics may serve as a reservoir poised to respond to changing environmental conditions in these dynamic systems.

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 score0.381
Threshold uncertainty score0.547

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 head0.005
GPT teacher head0.182
Teacher spread0.177 · 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

Citations30
Published2019
Admission routes2
Has abstractyes

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