MétaCan
Menu
Back to cohort
Record W2803868745 · doi:10.1093/femsec/fiy089

Fluctuations in populations of subsurface methane oxidizers in coordination with changes in electron acceptor availability

2018· article· en· W2803868745 on OpenAlexaff
Cara Magnabosco, Peer H. A. Timmers, Maggie C. Y. Lau, Gaëtan Borgonie, Borja Linage-Alvarez, Olukayode Kuloyo, Rose Alleva, Thomas L. Kieft, G. F. Slater, T. C. Onstott

Bibliographic record

VenueFEMS Microbiology Ecology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of TorontoMcMaster UniversityUniversity of Calgary
FundersUniversiteit van die VrystaatNational Science Foundation
KeywordsBiologyMethaneElectron acceptorAcceptorElectronChemical physicsEnvironmental chemistryEcologyBiochemistryCondensed matter physicsPhysics

Abstract

fetched live from OpenAlex

The concentrations of electron donors and acceptors in the terrestrial subsurface biosphere fluctuate due to migration and mixing of subsurface fluids, but the mechanisms and rates at which microbial communities respond to these changes are largely unknown. Subsurface microbial communities exhibit long cellular turnover times and are often considered relatively static-generating just enough ATP for cellular maintenance. Here, we investigated how subsurface populations of CH4 oxidizers respond to changes in electron acceptor availability by monitoring the biological and geochemical composition in a 1339 m-below-land-surface (mbls) fluid-filled fracture over the course of both longer (2.5 year) and shorter (2-week) time scales. Using a combination of metagenomic, metatranscriptomic, and metaproteomic analyses, we observe that the CH4 oxidizers within the subsurface microbial community change in coordination with electron acceptor availability over time. We then validate these findings through a series of 13C-CH4 laboratory incubation experiments, highlighting a connection between composition of subsurface CH4 oxidizing communities and electron acceptor availability.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.248
Teacher spread0.235 · 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

Citations27
Published2018
Admission routes1
Has abstractyes

Explore more

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