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Record W2019803892 · doi:10.1520/gtj11135j

Shear Displacement Dependent Strength of Municipal Solid Waste and Its Major Constituent

2001· article· en· W2019803892 on OpenAlexaff
S.G. Pelkey, AJ Valsangkar, Arvid Landva

Bibliographic record

VenueGeotechnical Testing Journal · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsCohesion (chemistry)Direct shear testGeotechnical engineeringShear (geology)Municipal solid wasteShear strength (soil)Triaxial shear testMaterials scienceGeologySoil waterEngineeringComposite materialSoil scienceWaste managementChemistry

Abstract

fetched live from OpenAlex

Abstract A limited amount of data exist on the shear strength properties of municipal solid waste. Similar to the soil strength parameters, the data on wastes are reported in terms of a cohesion intercept and an angle of internal friction. Most often the strength parameters reported are for the maximum values mobilized in laboratory testing. Recent state-of-the-art review papers on the topic have summarized the available strength data and noted that large shear displacements are required to mobilize peak shear strength parameters. In comparison, other components of a landfill system such as mineral and geosynthetic liners mobilize peak strengths at much smaller shear displacements. There are, therefore, shear displacement incompatibility issues that need to be resolved. In this paper the shear strength data from the direct shear tests performed on municipal solid waste samples and its major constituent (paper) are presented as a function of shear displacement. Results of a limited number of simple shear tests performed on municipal waste samples are also presented and compared with the data from direct shear testing.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.273
Teacher spread0.244 · 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 designBench or experimental
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

Citations73
Published2001
Admission routes1
Has abstractyes

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