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Record W2055712097 · doi:10.1081/ese-120002585

ASSESSING SANITARY LANDFILL STABILIZATION USING WINTER AND SUMMER WASTE STREAMS IN SIMULATED LANDFILL CELLS

2002· article· en· W2055712097 on OpenAlexaffabout
Roger Saint‐Fort

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsRoyal College of Physicians and Surgeons of CanadaMount Royal University
Fundersnot available
KeywordsLeachateEnvironmental scienceMunicipal solid wasteSTREAMSPollutionWaste managementLandfill gasContaminationEnvironmental engineeringEngineeringEcology

Abstract

fetched live from OpenAlex

This study was undertaken to provide a better understanding and to further define the stabilization processes involved in a typical municipal landfill representative of the city of Calgary, Canada, area. The objectives of this study were: (1) to characterize the composition of the solid waste constituents entering the landfill site, (2) to assess the relative decomposition of various waste components in the simulated test cells, (3) to parametize selected chemical and physical changes occurring during the stabilization process and (4) to determine water absorptive capacity of the different waste constituents. The results of the long term landfill stabilization using simulated landfill cell systems filled with winter and summer waste streams, respectively, have illustrated the potential changes that may occur with time with such systems. Based on the results, it can be inferred that the seasonal variation in waste composition deposited in a landfill will likely effect the rate of decomposition and settlement, chemical and physical characteristics of the leachate, moisture sorbing capacity of the site as well as variation in seasonal contaminants. Assuming that the results from the simulated landfills used during this study can be extrapolated to larger-scale landfill operations, it seems that summer waste streams pose a higher pollution threat to the environment than winter waste streams. The several trends observed in this study and the conclusions reported herein would have wide applications in landfill management.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.750

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 studies0.0000.001
Scholarly communication0.0000.002
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 head0.070
GPT teacher head0.320
Teacher spread0.250 · 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.

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

Citations7
Published2002
Admission routes2
Has abstractyes

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