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Record W4323567028 · doi:10.1061/ijgnai.gmeng-8040

Example Application of the Rescaling Equation for CPT Inferred State Parameters in Loose Mine Tailings

2023· article· en· W4323567028 on OpenAlexaboutno aff
Juan Ayala, Andy Fourie, David Reid

Bibliographic record

VenueInternational Journal of Geomechanics · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsIn situTailingsEquation of stateSample (material)GeologyGeotechnical engineeringSoil sciencePhysicsMaterials scienceThermodynamicsMeteorology

Abstract

fetched live from OpenAlex

This work reassesses the state parameters (ψ) inferred from in situ cone penetration testing (CPT) using normalized tip resistance (Qp) from the Rose Creek tailing impoundment in Canada that was previously introduced in the literature. For this reassessment, a recently proposed rescaling equation is used to modify the Qp−ψ trendline calculated using CPTwidget software (v2.5). These reassessed ψ values are compared with independent values calculated from in situ gravimetric water content (ψGWC) and the critical state line (CSL) measurements. A good agreement between the inferred ψ and the in situ sample ψGWC is obtained using the rescaling equation.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.498
Threshold uncertainty score0.252

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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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