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Record W2157888735 · doi:10.1177/0734242x09339325

Microbial methane oxidation processes and technologies for mitigation of landfill gas emissions

2009· review· en· W2157888735 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWaste Management & Research The Journal for a Sustainable Circular Economy · 2009
Typereview
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMethaneAnaerobic oxidation of methaneLandfill gasGreenhouse gasEnvironmental scienceWaste managementBioreactor landfillEnvironmental chemistryEnvironmental engineeringMethane emissionsAtmospheric methaneChemistryEngineeringEcology

Abstract

fetched live from OpenAlex

Landfill gas containing methane is produced by anaerobic degradation of organic waste. Methane is a strong greenhouse gas and landfills are one of the major anthropogenic sources of atmospheric methane. Landfill methane may be oxidized by methanotrophic microorganisms in soils or waste materials utilizing oxygen that diffuses into the cover layer from the atmosphere. The methane oxidation process, which is governed by several environmental factors, can be exploited in engineered systems developed for methane emission mitigation. Mathematical models that account for methane oxidation can be used to predict methane emissions from landfills. Additional research and technology development is needed before methane mitigation technologies utilizing microbial methane oxidation processes can become commercially viable and widely deployed.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.342
Teacher spread0.301 · 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