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Record W2788389357 · doi:10.1080/01490451.2017.1392652

Biogenic Methane Cycling in a Laboratory Model of an Abandoned Bituminous Coal Mine

2018· article· en· W2788389357 on OpenAlexfundno aff
Maija J. Raudsepp, Markus Fluggen, Adam Shypanski, Gene W. Tyson, S. D. Golding, Gordon Southam

Bibliographic record

VenueGeomicrobiology Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaQueensland Government
KeywordsCyclingMethaneEnvironmental scienceBituminous coalAsphaltCoalCoal miningEnvironmental chemistryWaste managementMining engineeringGeochemistryEnvironmental engineeringGeologyChemistryEcologyEngineeringGeographyArchaeologyBiology

Abstract

fetched live from OpenAlex

Microbial communities in decommissioned coal mines have the potential to promote methane generation. Here, two 1 m x 10 cm diameter column bioreactors designed to mimic an abandoned coal mine were monitored for a year, with zones of methanogenesis in the bottom, saturated waters and aerobic coal degradation and methane oxidation at the top. The resilience of aerobic methanotrophs to survive periods with low methane and oxygen conditions suggests methanotrophs may be useful in decreasing atmospheric methane fugitive emissions from decommissioned mines. When biogenic methane production from coal did occur, the rate was slow, ≤ 0.073 nmol CH4/g coal/day.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.233
Teacher spread0.221 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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