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Predicting the Uniaxial Compressive Strength and Static Young’s Modulus of Intact Sedimentary Rocks Using the Ultrasonic Test

2009· article· en· W2052622280 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Geomechanics · 2009
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCompressive strengthGeotechnical engineeringMaterials scienceModulusElastic modulusUltrasonic sensorGeologyComposite materialAcousticsPhysics

Abstract

fetched live from OpenAlex

The uniaxial compressive strength and static Young’s modulus (Es) of intact rocks are the most important geotechnical parameters for stability analysis of surface and underground structures. These parameters are obtained by the uniaxial compressive test. Although this test is simple, the preparation of the samples, especially of soft rocks, is a hard and time consuming task. By using a nondestructive method such as the ultrasonic test, one can indirectly predict the mentioned parameters. The uniaxial compressive and the ultrasonic tests were carried out on 64 samples of sedimentary rocks and, after regression analysis of the test results; best fit equations for predicting the uniaxial compressive strength and static Young’s modulus of these samples are proposed. Thus, in comparison with other proposed equations, these equations have larger value of accuracy and correlation coefficient (R2) . The equations are practical, simple, and accurate enough to apply and can be used in practice for the prediction purposes with acceptable accuracy.

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.

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: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.326

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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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