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Record W2320314069 · doi:10.1061/40970(309)43

Towards the Development of Sustainable Landfills

2008· article· en· W2320314069 on OpenAlexaff
Hsin‐Neng Hsieh, Jay N. Meegoda, J. P. A. Hettiarachi, Salah El Haggar, R. I. Stressel

Bibliographic record

VenueGeoCongress 2008 · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLeachateBioreactor landfillMunicipal solid wasteWaste managementLandfill gasEnvironmental scienceWaste collectionTruckEnvironmental engineeringEngineering

Abstract

fetched live from OpenAlex

Historically, municipal solid waste is mostly disposed in landfills. However, with the more stringent environmental regulations and difficulties in locating new waste disposal facilities, the low cost advantage of landfills is no longer true. This manuscript discusses the development of a new generation of landfills to achieve sustainable management of municipal solid waste. A sustainable landfill involves sequential application of anaerobic degradation, aerobic decomposition, and landfill mining. Biodegradation of waste in landfills is enhanced through leachate re-circulation, landfill gas collection, air injection, and environmental monitoring. Practical waste mining and recycling processes are also presented. This new generation of landfills will eliminate the commonly encountered problems of ground/surface water contamination and landfill gas emissions, as well as the need for new land for waste disposal and associated truck routing issues for new landfills.

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)0.003
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.022
GPT teacher head0.230
Teacher spread0.208 · 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 designTheoretical or conceptual
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

Citations12
Published2008
Admission routes1
Has abstractyes

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