MétaCan
Menu
Back to cohort
Record W4239149784 · doi:10.4133/1.3176711

Characterization of Solid Waste in a Bioreactor Landfill Using Seismic Borehole Methods

2009· article· en· W4239149784 on OpenAlexaffabout
Taryn E. Glancy, C. Samson, Paul J. Van Geel

Bibliographic record

VenueSymposium on the Application of Geophysics to Engineering and Environmental Problems 2009 · 2009
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsCarleton University
Fundersnot available
KeywordsBoreholeMunicipal solid wasteCharacterization (materials science)Environmental scienceWaste managementBioreactorBioreactor landfillGeologyPetroleum engineeringGeotechnical engineeringEngineeringMaterials scienceChemistry

Abstract

fetched live from OpenAlex

The biodegradation of solid waste in bioreactor landfills is dependant on a number of factors including moisture content. Identification of relatively wet and dry areas throughout the landfill would help operators determine where moisture should be added or not. This study attempts to utilize seismic borehole techniques to identify changes in seismic wave velocity through the waste due to the addition of moisture. The study is based on the principle that P‐wave velocity in a porous material increases with moisture content. The bioreactor landfill surveyed is located in Ste. Sophie, Quebec, Canada. Two vertical boreholes were installed 10 m apart and to a depth of 15 m, in order for vertical seismic profiles to be obtained. An initial characterization survey was conducted to understand seismic wave propagation through the waste. The P‐wave velocity is on the order 290–370 m/s and the S‐wave velocity is on the order of 140–175 m/s. Two‐day surveys were conducted to note changes in P‐wave velocity under relatively dry and wet conditions. There was no measurable change in P‐wave velocity after the addition of approximately 7000 L of water between the boreholes. This is most likely due to that fact that it was not possible to sample the area between boreholes where change was most likely to occur and it was not possible to control exactly where the water was being added.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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 designSimulation or modeling
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

Citations0
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueSymposium on the Application of Geophysics to Engineering and Environmental Problems 2009Same topicMineral Processing and GrindingFrench-language works237,207