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Record W2156142245 · doi:10.1038/ismej.2011.163

Microbes in thawing permafrost: the unknown variable in the climate change equation

2011· article· en· W2156142245 on OpenAlexafffund
David E. Graham, Matthew D. Wallenstein, Tatiana A. Vishnivetskaya, Mark P. Waldrop, Tommy J. Phelps, Susan M. Pfiffner, T. C. Onstott, Lyle G. Whyte, Elizaveta Rivkina, D. Gilichinsky, Dwayne A. Elias, Rachel Mackelprang, Nathan C. VerBerkmoes, Robert L. Hettich, Dirk Wagner, Stan D. Wullschleger, Janet Jansson

Bibliographic record

VenueThe ISME Journal · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsMcGill University
FundersLawrence Berkeley National LaboratoryOak Ridge National LaboratoryBiological and Environmental ResearchOffice of ScienceU.S. Department of EnergyEarth Sciences DivisionJoint Genome InstituteRussian Academy of SciencesUniversity of Tennessee, KnoxvilleMcGill UniversityPrinceton UniversityBattelle
KeywordsBiologyPermafrostClimate changeVariable (mathematics)EcologyAtmospheric sciencesComputational biologyMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

Considering that 25% of Earth's terrestrial surface is underlain by permafrost (ground that has been continuously frozen for at least 2 years), our understanding of the diversity of microbial life in this extreme habitat is surprisingly limited. Taking into account the total mass of perennially frozen sediment (up to several hundred meters deep), permafrost contains a huge amount of buried, ancient organic carbon ( Tarnocai et al., 2009 ). In addition, permafrost is warming rapidly in response to global climate change ( Romanovsky et al., 2010 ), potentially leading to widespread thaw and a larger, seasonally thawed soil active layer. This concern has prompted the question: will permafrost thawing lead to the release of massive amounts of carbon dioxide (CO 2 ) and methane (CH 4 ) into the atmosphere? This question can only be answered by understanding how the microbes residing in permafrost will respond to thaw, through processes such as respiration, fermentation, methanogenesis and CH 4 oxidation ( Schuur et al., 2009 ).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.147
GPT teacher head0.250
Teacher spread0.103 · 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 source (direct Gemma or distilled Codex), 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

Citations167
Published2011
Admission routes2
Has abstractyes

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Same venueThe ISME JournalSame topicClimate change and permafrostFrench-language works237,207