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Record W4247849601 · doi:10.32920/ryerson.14648640

Statistical evaluation of shear strength parameters of fine grained tills

2021· preprint· en· W4247849601 on OpenAlexaffabout
Chandra Prakash Poudyal

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCohesion (chemistry)Geotechnical engineeringFriction angleShear modulusMaterials scienceShear stressStress pathShear (geology)Triaxial shear testModulusGeologyComposite materialPhysics

Abstract

fetched live from OpenAlex

A statistical analysis is conducted in this study on the shear strength parameters of fine-grained tills from a series of consolidated undrained triaxial tests performed for a light rail transit project in the City of Toronto. Three different failure criteria are applied: the maximum stress ratio, the maximum deviator stress, and the residual stress. Three methods generate only minimal difference in the shear failure angle and a slight difference in cohesion. The friction angle calculated using the maximum stress ratio method ranges from 18.6 to 35.26 degrees compared with values ranging from 18.5 to 34.26 degrees by the maximum deviator stress method. The undrained shear modulus calculated from one-third and two-third peak deviator stress points generate a wide variation from 2 MPa to 167 MPa with an average value of 34 MPa.

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)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
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 head0.026
GPT teacher head0.256
Teacher spread0.230 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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