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Record W4294921303 · doi:10.1128/mra.00400-22

Draft Metagenome Sequences of the <i>Sphagnum</i> (Peat Moss) Microbiome from Ambient and Warmed Environments across Europe

2022· article· en· W4294921303 on OpenAlexaff
Bryan Piatkowski, Dana L. Carper, Alyssa A. Carrell, I-Min A. Chen, Alicia Clum, Chris Daum, Emiley A. Eloe‐Fadrosh, Daniel Gilbert, Gustaf Granath, Marcel Huntemann, Sara Jawdy, Ingeborg J. Klarenberg, Joel E. Kostka, Nikos C. Kyrpides, Travis J. Lawrence, Supratim Mukherjee, Mats B. Nilsson, Krishna Palaniappan, Dale A. Pelletier, Christa Pennacchio, T. B. K. Reddy, Simon Roux, A. Jonathan Shaw, Denis Warshan, Tatjana Živković, David J. Weston

Bibliographic record

VenueMicrobiology Resource Announcements · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsDalhousie University
FundersBiological and Environmental ResearchDivision of Environmental BiologyOffice of ScienceUT-BattelleOak Ridge National LaboratoryJoint Genome InstituteBattelleU.S. Department of EnergyNational Science Foundation
KeywordsPeatSphagnumMossMicrobiomeMetagenomicsEcosystemEcologyClimate changeEnvironmental scienceBiologyBioinformatics

Abstract

fetched live from OpenAlex

We present 49 metagenome assemblies of the microbiome associated with Sphagnum (peat moss) collected from ambient, artificially warmed, and geothermally warmed conditions across Europe. These data will enable further research regarding the impact of climate change on plant-microbe symbiosis, ecology, and ecosystem functioning of northern peatland ecosystems.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.999

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Study designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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