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Record W2241815540 · doi:10.2166/wst.2005.0566

Assessing the environmental burdens of anaerobic digestion in comparison to alternative options for managing the biodegradable fraction of municipal solid wastes

2005· article· en· W2241815540 on OpenAlexaffabout
Murray Haight

Bibliographic record

VenueWater Science & Technology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAnaerobic digestionBiogasWaste managementMunicipal solid wasteBiodegradable wasteEnvironmental scienceWaste treatmentMechanical biological treatmentEnergy recoveryEngineeringChemistryWaste collectionMethane

Abstract

fetched live from OpenAlex

Biological treatment processes including anaerobic digestion (biogasification) and composting are increasingly being considered by waste management officials and planners as alternatives for managing the mainly organic residues of municipal solid wastes (MSW). The integrated waste management model which is based upon the application of life-cycle analysis was employed to compare the environmental burdens of landfilling, composting and anaerobic digestion of MSW at a mid-sized Canadian community. Energy consumption (or recovery), residue recoveries and emissions to air and water were quantified. Scenario comparisons were analyzed to demonstrate that the environmental burdens associated with anaerobic digestion are reduced in comparison with the alternative options. The major benefit occurs as a result of the electricity produced from burning the biogas and then supplying the 'green power' to the local electrical grid.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.223
Threshold uncertainty score0.444

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.023
GPT teacher head0.308
Teacher spread0.285 · 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

Citations44
Published2005
Admission routes2
Has abstractyes

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