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Record W2903202412 · doi:10.3390/v10120672

Communities of Phytoplankton Viruses across the Transition Zone of the St. Lawrence Estuary

2018· article· en· W2903202412 on OpenAlexafffund
Myriam Labbé, Frédéric Raymond, Alice V. Lévesque, Mary Thaler, Vani Mohit, Martyne Audet, Jacques Corbeil, Alexander I. Culley

Bibliographic record

VenueViruses · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsCentre hospitalier de l'Université LavalUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhytoplanktonEstuaryBiologyBrackish waterEcologyHabitatSalinityOceanography

Abstract

fetched live from OpenAlex

The St. Lawrence hydrographic system includes freshwater, brackish, and marine habitats, and is the largest waterway in North America by volume. The food-webs in these habitats are ultimately dependent on phytoplankton. Viral lysis is believed to be responsible for a major part of phytoplankton mortality. To better understand their role, we characterized the diversity and distribution of two viral taxa infecting phytoplankton: the picornaviruses and phycodnaviruses. Our study focused on the estuary transition zone, which is an important nursery for invertebrates and fishes. Both viral taxa were investigated by PCR amplification of conserved molecular markers and next-generation sequencing at six sites, ranging from freshwater to marine. Our results revealed few shared viral phylotypes between saltwater and freshwater sites. Salinity appeared to be the primary determinant of viral community composition. Moreover, our analysis indicated that the viruses identified in this region of the St. Lawrence diverge from classified viruses and homologous published environmental virotypes. These results suggest that DNA and RNA viruses infecting phytoplankton are likely active in the estuary transition zone, and that this region harbors its own unique viral assemblages.

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 categoriesInsufficient payload (model declined to judge)
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 score0.193
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.281
Teacher spread0.253 · 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.

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

Citations8
Published2018
Admission routes2
Has abstractyes

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