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Record W2108838432 · doi:10.1139/s08-021

Field-scale treatment of landfill gas with a passive methane oxidizing biofilter

2008· article· en· W2108838432 on OpenAlexafffundvenueabout
Andrew Philopoulos, Christian Felske, Daryl McCartney

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsCanadian Natural ResourcesNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
FundersGovernment of CanadaFederation of Canadian Municipalities
KeywordsBiofilterOxidizing agentMethaneEnvironmental scienceWaste managementLandfill gasEnvironmental engineeringEnvironmental chemistryChemistryEcologyBiologyEngineering

Abstract

fetched live from OpenAlex

Municipal solid waste landfills are a major contributor to global methane emissions, a potent greenhouse gas. A treatment alternative was evaluated by installing three biogenic methane oxidizing biofilters into the landfill cover at the Leduc and District Regional Landfill (Alberta). Mature yard-waste compost was used as the biofilter medium. The results, collected over a period of 10 months, showed that two sites performed well as low surface emissions (<15 g CH4 m–2 d–1) were observed on 6 of 8 monitoring events. These two sites also demonstrated sufficient temperature (>20 °C) and moisture (>0.25 L L–1) levels to support a high level of biogenic activity, the former despite cold winter temperatures (<0 °C). The third site showed low calculated methane influent flows (<5 g CH4 m–2 d–1) and therefore observations of performance were limited.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.007
GPT teacher head0.188
Teacher spread0.181 · 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

Citations18
Published2008
Admission routes4
Has abstractyes

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