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Record W3194100603 · doi:10.1038/s41597-021-01005-7

Community composition of aquatic fungi across the thawing Arctic

2021· article· en· W3194100603 on OpenAlexaff
Mariana Kluge, Christian Wurzbacher, Maxime Wauthy, Karina E. Clemmensen, Jeffrey A. Hawkes, Karólína Einarsdóttir, Jan Stenlid, Sari Peura

Bibliographic record

VenueScientific Data · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversité LavalCenter for Northern StudiesUniversité du Québec à Chicoutimi
FundersUppsala Multidisciplinary Center for Advanced Computational ScienceScience for Life LaboratorySveriges Lantbruksuniversitet
KeywordsPermafrostThermokarstArcticEnvironmental scienceAquatic ecosystemTotal organic carbonDissolved organic carbonEnvironmental chemistryDetritusEcologyCarbon fibersSedimentBiogeochemistryBiologyChemistry

Abstract

fetched live from OpenAlex

Thermokarst activity at permafrost sites releases considerable amounts of ancient carbon to the atmosphere. A large part of this carbon is released via thermokarst ponds, and fungi could be an important organismal group enabling its recycling. However, our knowledge about aquatic fungi in thermokarstic systems is extremely limited. In this study, we collected samples from five permafrost sites distributed across circumpolar Arctic and representing different stages of permafrost integrity. Surface water samples were taken from the ponds and, additionally, for most of the ponds also the detritus and sediment samples were taken. All the samples were extracted for total DNA, which was then amplified for the fungal ITS2 region of the ribosomal genes. These amplicons were sequenced using PacBio technology. Water samples were also collected to analyze the chemical conditions in the ponds, including nutrient status and the quality and quantity of dissolved organic carbon. This dataset gives a unique overview of the impact of the thawing permafrost on fungal communities and their potential role on carbon recycling.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.156
GPT teacher head0.318
Teacher spread0.162 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

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