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Distribution and Diversity of a Protist Predator<i>Cryothecomonas</i>(Cercozoa) in Arctic Marine Waters

2012· article· en· W2158134464 on OpenAlexaffabout
Mary Thaler, Connie Lovejoy

Bibliographic record

VenueJournal of Eukaryotic Microbiology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBiologyProtistArcticEcologyFood webWater columnMeltwaterAbundance (ecology)PredationGlacier

Abstract

fetched live from OpenAlex

Heterotrophic nanoflagellates (HNFs) are key components in microbial food webs, potentially influencing community composition via top-down control of their favored prey or host. Marine cercozoan Cryothecomonas species are parasitoid and predatory HNFs that have been reported from ice, sediments, and the water column. Although Cryothecomonas is frequently reported from Arctic and subarctic seas, factors determining its occurrence are not known. We investigated the temporal and geographic distribution of Cryothecomonas in Canadian Arctic seas during the summer and autumn periods from 2006 to 2010. We developed a Cryothecomonas-specific fluorescent in situ hybridization (FISH) probe targeting ribosomal 18S rRNA to estimate cell concentrations in natural and manipulated samples. Comparison of simple and partial correlation coefficients showed that salinity, depth, and overall community biomass are important factors determining Cryothecomonas abundance. We found no evidence of parasitism in our samples. Hybridized cells included individuals smaller than any formally described Cryothecomonas, suggesting the presence of novel taxa or unknown life stages in this genus. A positive relationship between Cryothecomonas abundance and ice and meltwater suggests that it is a sensitive indicator of ice melt in Arctic water columns.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.387

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 head0.008
GPT teacher head0.206
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 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

Citations41
Published2012
Admission routes2
Has abstractyes

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