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Record W2420163264 · doi:10.1093/femsle/fnw151

A novel isolate and widespread abundance of the candidate alphaproteobacterial order (Ellin 329), in southern Appalachian peatlands

2016· article· en· W2420163264 on OpenAlexaff
Austin Harbison, Michael A. Carson, Louis J. Lamit, Nathan Basiliko, Suzanna L. Bräuer

Bibliographic record

VenueFEMS Microbiology Letters · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsLaurentian University
FundersNorthern Research StationJoint Genome InstituteU.S. Forest ServiceOffice of ScienceAppalachian State UniversityU.S. Department of Energy
KeywordsAcidobacteriaPeatEcologyProteobacteriaBiologyPlanctomycetesBacteria16S ribosomal RNA

Abstract

fetched live from OpenAlex

Peatlands of all latitudes play an integral role in global climate change by serving as a carbon sink and a primary source of atmospheric methane; however, the microbial ecology of mid-latitude peatlands is vastly understudied. Herein, next generation Illumina amplicon sequencing of small subunit rRNA genes was utilized to elucidate the microbial communities in three southern Appalachian peatlands. In contrast to northern peatlands, Proteobacteria dominated over Acidobacteria in all three sites. An average of 11 bacterial phyla was detected at relative abundance values >1%, with three candidate divisions (OP3, WS3 and NC10) represented, indicating high phylogenetic diversity. Physiological traits of isolates within the candidate alphaproteobacterial order, Ellin 329, obtained here and in previous studies indicate that bacteria of this order may be involved in hydrolysis of poly-, di- and monosaccharides. Community analyses indicate that Ellin 329 is the third most abundant order and is most abundant near the surface layers where plant litter decomposition should be primarily occurring. In sum, members of Ellin 329 likely play important roles in organic matter decomposition, in southern Appalachian peatlands and should be investigated further in other peatlands and ecosystem types.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.384

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)0.0000.000

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 head0.004
GPT teacher head0.178
Teacher spread0.174 · 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

Citations24
Published2016
Admission routes1
Has abstractyes

Explore more

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