MétaCan
Menu
Back to cohort
Record W2794540897 · doi:10.1093/femsec/fiy059

Activity and diversity of methane-oxidizing bacteria along a Norwegian sub-Arctic glacier forefield

2018· article· en· W2794540897 on OpenAlexfundno aff
Alejandro Mateos‐Rivera, Lise Øvreås, B.W. Wilson, Jacob C. Yde, Kai Finster

Bibliographic record

VenueFEMS Microbiology Ecology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersNorges ForskningsrådUniversity of British ColumbiaUniversitetet i BergenAarhus Universitet
KeywordsBiologyArcticPermafrostAbundance (ecology)GlacierEcologyAtmospheric sciences

Abstract

fetched live from OpenAlex

Methane (CH4) is one of the most abundant greenhouse gases in the atmosphere and identification of its sources and sinks is crucial for the reliability of climate model outputs. Although CH4 production and consumption rates have been reported from a broad spectrum of environments, data obtained from glacier forefields are restricted to a few locations. We report the activities of methanotrophic communities and their diversity along a chronosequence in front of a sub-Arctic glacier using high-throughput sequencing and gas flux measurements. CH4 oxidation rates were measured in the field throughout the growing season during three sampling times at eight different sampling points in combination with laboratory incubation experiments. The overall results showed that the methanotrophic community had similar trends of increased CH4 consumption and increased abundance as a function of soil development and time of year. Sequencing results revealed that the methanotrophic community was dominated by a few OTUs and that a short-term increase in CH4 concentration, as performed in the field measurements, altered slightly the relative abundance of the OTUs.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.010
GPT teacher head0.210
Teacher spread0.199 · 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

Citations19
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueFEMS Microbiology EcologySame topicMethane Hydrates and Related PhenomenaFrench-language works237,207